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Digital Twin
Envrionment

Offers a range of environments specifically designed for the development of autonomous robots, from indoor settings such as offices and residential spaces, to outdoor environments such as pedestrian roads.

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Validation of autonomous vehicles can be conducted with MORAI SIM: Drive, which includes simulation environments, sensors, and vehicle models identical to the real world.

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Infrastructure Digital Twins

Connect The Physical And Virtual Worlds

Synchronize work, gain greater visibility, and make sense of the right data at the right time.

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Bentley Systems | Infrastructure Engineering Software Company

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Infrastructure Digital Twins | Bentley Systems Software

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Take a look at what Digital Twins are, how they benefit you, and how it all works!

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This guide will help you understand exactly what a digital twin is and how you can use it to manage your operations in real-time.

After reading this guide, you’ll know about:

The different types of digital twins

How to use AI & machine learning with digital twins

Blockchain & digital twins

How to design digital twin applications

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The XMPro Digital Twin Definition

A digital twin is an instance of a digital model that represents an entity, which includes assets, processes, and systems which are sufficient to meet the requirements of a set of use cases.

I'll expand on this definition to explain each of those concepts.

Digital Model

A digital twin model typically describes the characteristics, attributes, and behavior of an entity type.

If you take a Warman AH slurry pump as an example of an entity type, you will create a digital model for that type of pump. It would consist of various data types like time-series data, analytical models, and 3D models (we cover all six data types later in this guide). You can have a hundred different pumps of the same kind that all use a standardized model.

Instance

A crucial part of our definition of a digital twin is that it is an instance of a digital model.

You might have a hundred Warman AH slurry pumps that use the same model. However, each pump's instance of that model creates a unique digital twin.

The digital twin for each pump uses the same model as others of the same type, but each pump has a unique instantiation with unique information.

Watch the video below for a simple explanation of this concept.

Data in a digital twin usually doesn't come from a single source. It's important to understand that a digital twin is not a single massive data lake that contains all the information about an entity.

It's about the way the model describes where the information lives. The model is not the digital twin. The model is a description of characteristics, attributes, and behaviors that define what a digital twin's structure looks like, but the twin is the unique instance for a specific entity.

The Oxford Dictionary defines an entity as, "a thing with a distinct and independent existence."

Our digital twin definition explicitly says that an entity includes assets, processes, and systems. You can build digital twins of more than just your physical assets. I'll explain more about this in the section on the types of digital twins.

What we mean by "sufficient to meet the requirements of a set of use cases," is that the idea is not to create an uber digital twin that can do everything for everybody.

Your banking app is the digital twin of your financial health. It's not the same as the twin that describes your travel plans or your training regime for a triathlon.

Industrial Digital Twin Categories

XMPro's Industrial Digital Twins is modelled based on 2 primary patterns:

Discrete or atomic Digital Twins

Composite Digital Twins

Composite Assembly Twin

Composite System Twin

Discrete Digital Twin

A discrete Digital Twin is the lowest level of abstraction that is still sufficient to meet the requirements of a specific use case. It is often a single or atomic entity where it adds no value to break it down in components or parts, e.g. the gearbox or motor for a Ball Mill in mining. It doesn't need to be broken down into the sub-parts as the status and monitoring is reported at this entity level.

Composite Digital Twin

A composite Digital Twin is a combination of discrete Digital Twins that represent an entity comprised of multiple individual components or parts. A composite Digital Twin can be an Assembly Twin like a Ball Mill in Mining or a System Twin that comprises multiple Assembly Twins such as the Processing and Refinement Plants.

It can be depicted as a cube with the sides representing data from the six data types I explain in chapter 6.

How to Create Digital Twin Applications

XMPro Digital Twin Reference Architecture

The XMPro Digital Twin Reference Architecture is primarily focused on twins for owner-operators in asset intensive industries such as mining, oil and gas, and energy and utilities. It is also focused on operational and continuous intelligence applications where the twins are continuously updated with real-time information from sensors and other services such as weather, maintenance systems, or oil analysis laboratories.

The reference architecture above shows how you can use XMPro's Agile Application Studio to design and run Digital Twins using our Integrate, Orchestrate and Operate approach.

The architecture is structured around the "use case" principle, and the example above demonstrates the status, operational and simulation twin scenarios.

The primary data sources are based on the six dimensions explained earlier. Themes such as trustworthiness, integration and connectivity are implicitly part of the architecture.

The three key focus areas of the architecture are:

Create a Minimum Viable Digital Twin

We advise that you start by building a minimum viable version of your digital twin to test your assumptions. We've adapted this idea from the Lean Startup approach that has gained popularity in recent years.

By building a minimum viable twin, you can start small, test your assumptions, learn from feedback, and improve rapidly.

Here's how we recommend building your first digital twin:

Step 1: Start with the Job You Want Your Digital Twin to Do

Think about your digital twin like you would about hiring a person. What job would you want them to do? Figure out what data you need to collect, what decisions the twin will need to make, how it would notify you of critical events, and what actions need to be taken to respond to those events.

Do you recall the digital twin definition from the beginning of this guide? We said that it needs to be a digital representation that is sufficient to meet the requirements of a specific set of use cases.

When you think about a set of use cases, you're asking, "What is the business problem I'm trying to solve?" It's important to emphasize that a digital twin is not an uber twin that does everything for everybody. The smart way to design a digital twin is to build it around a specific challenge.
Questions to Ask When Planning a Digital Twin:

1. Does it need to continuously monitor something and let you know when an event occurs?

2. Should it provide decision support or decision automation, where it applies business rules or looks for anomalies?

3. Can it apply machine learning or artificial intelligence? Phrased another way, if your digital twin was a real person, would you like them to use their intelligence and interpret the data?

4. Should your digital twin make a recommendation on what to do next, or would you want it to take action on your behalf?

Step 2: Design the Real-Time Data Flow

In the first step, you can use XMPro's Data Stream designer to visually design the real-time flow of data. You can connect to your different data sources, add in analytics, and trigger recommendations or workflows.

Once you have the data stream set up, you can move on to creating the visual aspect of the twin that will provide situational awareness to your users.

While you can automatically trigger actions with XMPro's Data Streams, many organizations still prefer showing data to a real person to make the decision. In this case, you can send your data to a real-time XMPro application or a dashboard in a third-party tool.

Step 3: Create the Visualization & Actions

Providing the user with this real-time visualization of the data will help them understand what happened, why it happened, what the trends are, and even what the recommended actions are. With XMPro's Application Designer, you can build digital twin applications that provide all of this real-time information in a single interface.

Step 4: Iterate & Improve

As you deploy your digital twin application into the real world, you are bound to learn things you never expected. It might be more challenging to get access to the data. You might uncover that your operational problems are more significant than you thought.

You could also learn that this twin could be scaled out to solve this same issue across multiple plants in your organization for even greater ROI.

With XMPro's Data Stream and App Designer, you can easily tweak your digital twin, ensuring it delivers on the job you hired it to do.

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Download the exclusive guide to digital twins - XMPRO

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This guide will help you understand exactly what digital twins are and how you can use them to manage your operations in real-time.

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OpenSimulator can be used to simulate virtual environments similar to Second Life™. However, OpenSimulator does not aim to become a clone of the Second Life server platform. Rather, the project aims to enable innovative feature development for virtual environments and the Metaverse at large.

OpenSimulator is getting more stable over time but is still a high complex software system that can suffer various bugs and quirks; handle with care!

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In the age of the Internet of Things, it is critical for smart factories to have seamless device integration and communication. With factories having multiple automated systems, the challenge is how to effectively achieve greater efficiency through equipment autonomy; this is the goal of Swarm Autonomy. With AMR autonomous robots and a 5G private network, ADLINK is helping manufacturing industries upgrade their systems from automation to autonomous.

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Easy Integration

Legacy & new facility integration

Cross-brand integration

IT and OT integration

High Flexibility

Robot & warehouse control system connectivity

Satisfy High-Mix Low-Volume manufacturing applications

Real-time synchronous communication between robots, conveyors, and racks

High OEE

Shortens integration, configuration, and deployment time

24/7 operating via smooth integration capability

SMR250 series

1.5 m/s max speed with 250 kg full loading

Learn More

SMR1000 series

1.0 m/s max speed with 1000 kg full loading

Learn More

Heterogeneous Integration

With Swarm Core software, AMR can easy integrate and communicate with third-party OT equipment and IT systems

Innovative Fleet Management

Event-based control management with dynamic re-scheduling capability and intelligent dispatch system

Accurate Docking Performance

Up to 50% more accurate docking system within 5mm compared to other AMRs

Dynamic Parameter Zone Setup

Based on the top-module type and operating environment, the AMR can adjust safe distance and speed to increase safety

Brochure Swarm Autonomy Solution Optimized Production Efficiency with Autonomous Mobile Robots

Guidebook Automated Material Handling Made Simple with SWARM TOOLS

Brochure ADLINK 5G private network all-in-one solution

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Autonomous Mobile Robots | Swarm Autonomy | ADLINK

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ADLINK is helping manufacturing industries upgrade their systems from automated to autonomous, achieving greater efficiency with autonomous robots and a 5G private network.

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Images are unavailable offline.

A Husky robot, left, and a Jackal robot at the Clearpath Robotics warehouse in Kitchener, Ont. The Waterloo-based robotics company has been sold to Rockwell Automation Inc.

Hannah Yoon/The Canadian Press

American industrial automation giant Rockwell Automation Inc. ROK-N has agreed to buy Waterloo, Ont. autonomous robot maker Clearpath Robotics Inc., in a deal that could exceed US$600-million in value.

Rockwell announced the deal last week, and did not disclose the price. But four sources familiar with the matter said Rockwell is paying between US$550-million and US$600-million upfront, and that the total payout to shareholders could top US$600-million if Clearpath meets undisclosed performance targets. The Globe and Mail is not identifying the sources because they were not authorized to discuss the matter publicly.

Clearpath chief executive Matthew Rendall declined to comment on the deal. Rockwell declined to comment in detail, saying only that Clearpath would become part of the company's intelligent devices division.

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The deal, which is expected to close this year, resulted from a competitive process in which Rockwell significantly outbid other strategic buyers, two of the sources said. It is the culmination of a lengthy period dating to last year in which the Canadian company had pursued a range of options, including raising growth financing or selling all or part of the enterprise.

The deal is a big win for many Canadian investors that have financed 14-year-old Clearpath. Those include several Waterloo-region angel investors such as Larry Innanen and Mike Stork, who is a former Clearpath board member. The company's other backers include Canadian funds Inovia Capital, Kensington Private Equity Fund, BMO Capital Partners, McRock Capital, Garage Capital, Export Development Canada and Laurence Capital. Among Clearpath's foreign investors are Mitsubishi Electric Corp., RRE Ventures, Caterpillar Ventures and GE Ventures.

The deal is Inovia's second money-making sale from its portfolio this year in the smart factory space, after Swedish enterprise technology giant IFS World Operations AB's purchase of Quebec City-based Poka Inc., maker of a social-network platform for factory operations, for about US$200-million.

In a news release, Rockwell said Clearpath and its fast-growing subsidiary OTTO Motors are expected to contribute a percentage point to Rockwell's revenue growth in the 2024 fiscal year. Rockwell has forecast it will generate about US$8.9-billion in revenue this year, which would translate into forecast sales of about US$90-million from Clearpath next year.

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One of the sources said Clearpath is currently generating revenue at an annualized rate of US$50-million to US$75-million, based on the rapid growth of its eight-year-old OTTO division, which focuses on selling to the automotive, consumer packaged goods and home appliance manufacturing sectors. The division's customers include global manufacturing giants General Electric, Toyota and Nestle.

OTTO's strong demand and rapidly growing order book reflect broader trends. Manufacturers are shaking up their supply chains amid a reordering of the geopolitical environment, reshoring facilities to home markets, and, in the process, ramping up automation in response to labour shortages. Several vendors to manufacturers have prospered from that shift, including Clearpath, whose robots are seen as tools for cutting down on costs and increasing efficiencies, the source said.

Clearpath was founded in 2009 by four University of Waterloo mechatronics engineering grads: Mr. Rendall, Ryan Gariepy, Pat Martinson and Bryan Webb. The founders set out to create a company "dedicated to automating the world's dullest, dirtiest, and deadliest jobs," Clearpath says on its website. Initially it created technology to remove mines from war zones, then shifted in the early 2010s to making driverless vehicles to perform hazardous jobs in manufacturing and industrial plants.

The company shifted its strategy further in 2015, with the launch of OTTO. Clearpath raised more than US$88-million in funding prior to the Rockwell sale.

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Waterloo's Clearpath Robotics sold to Rockwell Automation for US$600-million plus - The Globe and Mail

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Deal locks in gains for Canadian investors including Inovia, McRock Capital

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SSR is a one-stop shop for everything you need to launch your tele-operated robotic ROVER. From positioning to perception and machine control, we curate high-performance receivers, sensors, computing and software to operate your telepresence applications. Not only that, but we’ll put it all together for you on the platform of your choice — from concept to completion.

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Bring your Remote ROVER to life

Autonomous vehicles (AVs) are an essential piece of equipment to enable autonomy research, but they aren’t off-the-shelf. The research program goals affect the choice of sensors, software modules and vehicle configuration. It can take years for researchers to get a platform up and running from scratch.

The trick is to not reinvent the wheel. This is where the experts at SSR come in. We help you build the right automotive platform to suit your research goals.

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Benefits of working with Tele-operated system

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Benefits of working with Tele-operated system

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Vetted autonomy software

Wide range of platforms

Trusted autonomy experts

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Step-by-step specification of your own R&D vehicle platform, from the vehicle to sensors, software and storage

Your AutonomouStuff platform purchase includes training on the use of:

Platform

Components

Software

When you purchase a platform from AutonomouStuff, we’re part of your team. A knowledgeable and experienced project manager stays in touch with you on a regular basis to keep you current on platform updates and to make sure we’re meeting your needs.

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An AutonomouStuff exclusive, the Autoware Kit includes the latest in high-end industrialized computing, 3D LiDAR, automotive radar and positioning technology. An advanced software stack provides many of the necessary tools for navigating difficult urban environments.

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Kit includes:

AStuff Spectra

NovAtel PwrPak7D-E2 (Kit 2.5)

Aptiv ESR 2.5

Allied Vision Mako G-319C

Velodyne Ultra Puck

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Our software development program, which has its roots in the DARPA challenges, is based on:

Decades of robotics experience.

Unique industry knowledge and perspective.

Expertise in control algorithms and perception sensing.

Extensive experience with middleware (Robot Operating System [ROS]) for self-driving applications.

An agile process based on rapid iteration and validation that meets software requirements with a high degree of quality control.

Collaboration with our global partner ecosystem.

We develop modular software, built on ROS middleware, that you can plug into your own systems and software.

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Automotive

An AutonomouStuff automotive platform provides a safe, reliable, robust solution for developing and deploying automated driving applications.

LEARN MORE

NEV

Electric AutonomouStuff platforms are designed for concept demonstrations and use where a full-size vehicle with a combustion engine can't operate.

LEARN MORE

Class 8

AutonomouStuff platforms for shipping deliver the same safe, reliable and robust solutions as our other platforms, but on a larger scale.

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Shuttle Automation

Advanced control for autonomous shuttle programming

LEARN MORE

Speed and Steering Control

Programmable emulation of typical human driving behavior

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ROVer platforms

A range of safe, reliable, robust platforms for developing and deploying automated driving systems for a variety of autonomous applications — from shuttles to semis.

TOR kits

All the tech you need for positioning, sensing and computing that work with various open-source software options, and data storage scaled to suit your application.

TOR software

Tap into our decades of experience vetting and contributing to open-source autonomy software so it works with your own systems and gets your platform up and running fast.

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web reference

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Secure expert help with hardware and software integration, sensor selection, technology solutions and training.

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[$316M] SARCOS TECHNOLOGY & ROBOTIC CORPORATION

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[$316M] SARCOS TECHNOLOGY & ROBOTIC CORPORATION

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Sarcos Technology and Robotics Corporation is acquiring RE2 Robotics, a Pittsburgh-based developer of autonomous and teleoperated mobile robotic systems, for $100 million. The deal consists of $30 million in cash and $70 million of Sarcos common stock. The deal is expected to close in the second quarter of 2022.

https://www.therobotreport.com/sarcos-acquiring-re2-robotics-for-100m/

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AWS: ReInvent 2023 — Aerodyne and Amazon collaborate to build drone data solutions

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AWS: ReInvent 2023 — Aerodyne and Amazon collaborate to build drone data solutions

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AWS:ReInvent 2023 — Aerodyne and Amazon collaborate to build drone data solutions

AWS:ReInvent 2023 — Aerodyne and Amazon collaborate to build drone data solutions

By Kiran Jacob / theedgemalaysia.com

30 Nov 2023, 03:22 pm

(Nov 30): Aerodyne group is set to run its DRONOS software as a service (SaaS) platform on Amazon Web Services to help drone operators worldwide grow their businesses.

DRONOS is an end-to-end drone service platform that allows users to onboard, analyse and make sense of drone data to optimize operations, drive efficiencies and conduct aerial inspections.

Notably, Aerodyne operates drone solutions for telecommunications, agriculture, surveillance, logistics and energy industries in 45 countries.

“DRONOS is a drone operating system. When you fly drones, you need to have expertise [whether] for the pilot or crew to process the data. We want to democratize this. Rather than relying on some experts, we are putting all of this within DRONOS,” said Kamarul A Mohamed, founder and group CEO of Aerodyne.

“It means that anybody can then get drone intelligence and data intelligence. It’s not just drones. You can take satellite data, ground data, you can go out and take your own photos and dump them into the system. We can then extract intelligence for you to make the right decisions on time and every time.

“The whole idea is to connect the whole ecosystem seamlessly for everyone. We are proud to be working with AWS to bring this technology to the market.”

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(Nov 30): Aerodyne group is set to run its DRONOS software as a service (SaaS) platform on Amazon Web Services to help drone operators worldwide grow their businesses.

DRONOS is an end-to-end drone service platform that allows users to onboard, analyse and make sense of drone data to optimise operations, drive efficiencies and conduct aerial inspections.

Notably, Aerodyne operates drone solutions for telecommunications, agriculture, surveillance, logistics and energy industries in 45 countries.

"DRONOS is a drone operating system. When you fly drones, you need to have expertise [whether] for the pilot or crew to process the data. We want to democratise this. Rather than relying on some experts, we are putting all of this within DRONOS," said Kamarul A Mohamed, founder and group CEO of Aerodyne.

"It means that anybody can then get drone intelligence and data intelligence. It's not just drones. You can take satellite data, ground data, you can go out and take your own photos and dump them into the system. We can then extract intelligence for you to make the right decisions on time and every time.

"The whole idea is to connect the whole ecosystem seamlessly for everyone. We are proud to be working with AWS to bring this technology to the market."

Using the Amazon Simple Storage Service (Amazon S3), Aerodyne created a data lake on AWS to store and turn drone data into actionable insights. Furthermore, using Amazon SageMaker, Aerodyne has been able to automate analysis on mobile phone towers and farm fields.

Aerodyne has also reduced its customers' cellular tower operational costs by an average of 20% by using AWS. Additionally, manual data processing costs have reduced by more than 70% compared to on-premises infrastructure.

Aerodyne's move with AWS will allow them to get to market faster. By leveraging on AWS, Aerodyne will be able to accelerate their plans to deliver DRONOS which initially would have taken about 18 months, said Kamarul.

"In the past, we grew with mergers and acquisition (M&A) strategies. We started this in 2018, and up to now we have completed 21 M&As. Those give us boots on the ground and leadership in the different regions. With the release of this new technology, we do not need boots on the ground. We are 'uberising' this if you like," he said.

"Our competitors [can] now be our pilots, they can be doing the flying themselves, and we are enabling more people to get into this. We cannot be in 150 countries by ourselves. With the rollout of DRONOS we can work with any company,"

"We will enable them to serve these complex requirements with complex customers, which they otherwise would not have been able to serve. By working with established names such as AWS, it gives us the structure to give the conviction and confidence to the end user that this is all running in a secure environment."

Kamarul also said he aims to bring data intelligence to every corner of the world without having to physically be there. Aerodyne will have a certification programme for small drone companies, or mom and pop drone companies, as Kamarul put it, to enable them to operate different types of projects.

Aerodyne also plans to experiment with AWS's generative artificial intelligence capabilities to build a large language model. This will be able to help companies to better plan drone flights and visualise close to one petabyte of drone data.

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AWS:ReInvent 2023 - Aerodyne and Amazon collaborate to build drone data solutions

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Aerodyne group is set to run its DRONOS software as a service (SaaS) platform on Amazon Web Services to help drone operators worldwide grow their businesses. DRONOS is an end-to-end drone service platform that allows users to onboard, analyse and make sense of drone data to optimise operations, drive efficiencies and conduct aerial inspections.

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RE2 provides the RE2 Sapien family of robotic arms, RE2 Detect computer vision software, and RE2 Intellect autonomy software to enable intelligent mobile manipulation systems that operate in a variety of complex indoor and outdoor environments. RE2’s systems help companies in the aviation, construction, defense, energy, and medical industries to enable remote operations, improve worker safety and efficiency, and reduce operational costs. RE2 is based in Pittsburgh, Pennsylvania.

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We built Mergr to save people the arduous and time-consuming process of tracking when companies are bought, sold, and who currently owns them.

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RE2, Acquired by Sarcos Technology and Robotics Corp. on March 28th, 2022 | Mergr

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RE2 was acquired by Sarcos Technology and Robotics on March 28, 2022

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Solving the labor shortage in logistics with human-centered remote operation

Phantom enables people to remotely control vehicles across sites from thousands of miles away — with just the click of a button.

Phantom enables people to remotely supervise, assist, and drive vehicle fleets from thousands of miles away.

https://phantom.auto

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FERNRIDE RAISES $31M IN SERIES A FUNDING

Fernride Raises $31M in Series A Funding

GERMANY

Published on June 16, 2023

Fernride, a Munich, Germany-based autonomous, electric trucking company, raised $31M in Series A funding.

Backers included 10x Founders, Promus Ventures, Fly Ventures, Speedinvest, and Push Ventures along with corporate investors, such as HHLA Next, DB Schenker via Schenker Ventures and Krone.

The company intends to use the funds to accelerate the transition towards automated and sustainable logistics, scale operations with existing and new customers globally and boost the technological development of their approach to human-assisted autonomy.

Founded by Hendrik Kramer, Maximilian Fisser, and Jean-Michael Georg, Fernride offers scalable automation solutions for yard trucking that increase productivity, promote sustainability, and improve worker safety. The company employs a human-assisted automation approach, which allows for remote takeovers of electric trucks when necessary. This ensures integration and reliable operations for logistics operators.

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About

Ottopia is a teleoperation software company providing a platform that enables humans to safely control any type of vehicle from afar.

Funding

Ottopia has raised a total of $26.5M in funding over 3 rounds. Their latest funding was raised on Jan 10, 2023 from a Series A round.Ottopia is funded by 9 investors. AI Alliance Fund and MizMaa Ventures are the most recent investors.

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Refraction AI is a leading robotics delivery software and services startup.

Refraction AI is a leading robotics delivery software and services startup. It builds and deploys robotic platforms for providing safe and scalable last-mile goods delivery in urban areas. Refraction picks up goods from places like restaurants, pharmacies, and grocery stores and brings them directly to the door, enabling faster, cheaper, and safer

delivery to meet customer’s growing expectations.

Refraction’s robots are completely autonomous using a system of a dozen cameras, radar, and ultrasonic sensors and can also be teleoperated and monitored remotely. They employ an autonomy stack that is designed to perform in all climates, from the harshest of winters of Michigan to the hottest summers of Texas.

Funding

Refraction AI has raised a total of $10.7M in funding over 4 rounds. Their latest funding was raised on Mar 2, 2022 from a Seed round.Refraction AI is funded by 7 investors. Alumni Ventures and Chad Laurans are the most recent investors.

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Halo Car, a Las Vegas-based startup that combines teleoperations and car sharing, said it will remove the human safety operator from behind the wheel later this year - the last hurdle before its commercial launch.

The milestone would mean Halo Car will use humans to remotely control vehicles through public streets and deliver them to its car-sharing service customers. These fully remote deliveries will mark the official launch of commercial operations and kick off a campaign to scale its fleet of electric vehicles and expand beyond Las Vegas.

The unique approach to car sharing has attracted several investors. The company said Wednesday it raised $5 million in a seed round led by climate tech fund At One Ventures, with participation from T-Mobile Ventures, Earthshot Ventures and existing investor Boost VC. The funds will help the startup expand into cities beyond Las Vegas and scale its fleet to 1,000 EVs by the end of 2023.

Halo Car's model shouldn't be confused with autonomous vehicle technology companies like Argo AI, Aurora, Cruise, Waymo and Zoox, which have developed self-driving systems designed to allow vehicles to navigate public streets without any human in the loop - either behind the wheel or remotely. Halo Car's model provides remote human assistance at all times.

Halo Car's business model crosses Zipcar, which requires customers to pick up the car wherever the previous user parked it, with traditional rental car companies such as Enterprise and Rent-A-Car. However, Halo Car delivers the vehicle directly to the next customer; think white-glove chauffeur service, without the white gloves or the chauffeur.

Founder and CEO Anand Nandakumar led perception for Uber's self-driving unit Advanced Technologies Group. He developed the idea of using remote piloting in 2019 after leaving Uber. Looking at the 10-year horizon for fully autonomous driving, he thought remote human piloting could serve as a bridge to deploying driverless cars sooner.

Halo Car's remote operators work out of the company's Las Vegas headquarters, using T-Mobile's Ultra Capacity midband 5G network, as well as extended range low-band 5G networks and on LTE when needed, to transmit video and data from the cars to a driving simulator. The human operator sits in the simulator, which features an oversized TV monitor, a steering wheel, pedals and a gearshift, and watches for pedestrians, bicyclists, cars, trash cans and other obstacles when the car is in driverless mode.

The remote pilot disconnects from the car once the customer is granted keyless access through Halo Car's app. When they're done, they leave the car for the remote human operator to retrieve and return it to headquarters, where it is cleaned, charged and parked waiting for the next ride.

If the vehicle loses connection to 5G networks, it is brought to a full stop.

Halo Car completed beta testing in Las Vegas earlier this year using two Kia Niro EVs retrofitted with six cameras but no radar, lidar or ultrasonics, a pared-down approach favored by Tesla. Past iterations of Halo Car's technology stack used nine cameras, radar and ultrasonics to support the remote controlled operations.

During the beta phase, support operators sat inside the cars to oversee the remote piloted deliveries and were picked up and driven back to headquarters by a Halo Car employee.

Nandakumar positions Halo Car as a more cost-effective and convenient way to rent an EV without worrying about parking. The vehicles, which can be rented by the hour or at a flat daily rate, could help manufacturers increase their visibility and get more potential customers to try EVs. Both General Motors and Polestar are using that playbook, inking deals to supply Hertz's rental fleet with up to 240,000 EVs over the next five years.
Clarification: Nandakumar developed the idea of Halo Car in 2019, after leaving Uber. The article has been adjusted to reflect the proper timing.

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Halo Car's teleoperated car-sharing service to roll out this year with no one behind the wheel | TechCrunch

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Halo Car, a Las Vegas-based driverless electric carshare, raised a $5 million seed round to begin removing human support from the car.

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About

DriveU.auto is a US-based developer of a connectivity platform for autonomous vehicle teleoperation.

Funding

DriveU.auto has raised a total of $4M in funding over 1 round. This was a Seed round raised on Jun 23, 2020.DriveU.auto is funded by 4 investors. Kaedan Capital and Yigal Jacoby are the most recent investors.

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About

Sentante is a company that develops robotic teleoperated systems for endovascular procedures.

Kaunas, Kauno Apskritis, Lithuania

11-50

Non-equity Assistance

Private

sentante.com

79,161

Funding

Sentante has raised a total of €2.5M in funding over 3 rounds. Their latest funding was raised on Jun 6, 2023 from a Non-equity Assistance round.Sentante is funded by 2 investors. MedTech Innovator and European Innovation Council are the most recent investors.

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1) Formant acquired Formation for an undisclosed amount

2) Iveco Defence Vehicles acquired MIRA-Unmanned Ground Vehicles for an undisclosed amount

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Bentley's iTwin platform is an open, scalable cloud platform that provides APIs and services to help developers create digital twin applications for project teams and owner-operators to create, visualize, and analyze digital twins of infrastructure assets.

The platform takes care of back-end concerns such as security, infrastructure, and data integration so that developers can focus on building applications and bringing them to market faster.

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Bentley's iTwin platform is an open, scalable cloud platform that provides APIs and services to help developers create digital twin applications for project teams and owner-operators to create, visualize, and analyze digital twins of infrastructure assets.

The platform takes care of back-end concerns such as security, infrastructure, and data integration so that developers can focus on building applications and bringing them to market faster.

Bentley's iTwin platform is the foundation for iTwin Enabled applications and digital twin solutions created by Bentley and its strategic partners, digital integrators, system integrators, independent software vendors, and software developers.

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Bentley's iTwin platform is the foundation for iTwin Enabled applications and digital twin solutions created by Bentley and its strategic partners, digital integrators, system integrators, independent software vendors, and software developers.

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About Ocean Infinity

Ocean Infinity is a company that focuses on large scale marine robotic operations within the maritime industry. The company's main services include the deployment of robotic technologies to capture ocean data and deliver maritime solutions, with a particular emphasis on minimizing environmental impact. Ocean Infinity primarily serves sectors such as energy, telecommunications, government, defense, and science & research. It was founded in 2017 and is based in Houston, Texas.

Ocean Infinity has sealed its fifth acquisition this year, buying Norwegian technology developer for autonomous port operations Red Rock. According to the Houston-based marine robotics firm, Red Rock is spearheading the development of digital and autonomous solutions to revolutionise lifting and handling both onshore and offshore.

The acquisition will combine Ocean Infinity’s Armada robotic vessels and low emission operations with Red Rock’s ability to develop hardware and software solutions for remote and autonomous handling. “Together, the two businesses will transform port operations and shipping through artificial intelligence-enabled, safe, low emission movement of vessels and cargo,” Ocean Infinity said.

All of Red Rock’s business lines spanning marine, artificial intelligence, software solutions and digital consulting are included as part of the acquisition. Ocean Infinity’s footprint in Europe now extends to offices in Norway and Romania, alongside the existing presence in North America, the Middle East and Africa. The enlarged group will have a full-time headcount of approximately 600 people.

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FIWARE, the Open Source Platform for Our Smart Digital Future

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FIWARE, the Open Source Platform for Our Smart Digital Future

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A framework based around supplying a cornerstone function required in any smart solution: the need to manage context information, enabling to perform updates and bring access to context.

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SARCOS Financial statement 8mill revenue

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Digital twin is a dynamic, virtual representation of its physical counterpart, usually across multiple stages of its lifecycle. It uses real-world data combined with engineering, simulation or machine learning models to enhance operations and support human decision making. Digital Twin mirrors a unique physical object, process, organisation, person or other abstraction and can be used to answer what-if questions, present insights in an intuitive way and provide a way to interact with the physical object/ twin.

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Figure 1: Digital Twin Context
Digital twin is a dynamic, virtual representation of its physical counterpart, usually across multiple stages of its lifecycle. It uses real-world data combined with engineering, simulation or machine learning models to enhance operations and support human decision making. Digital Twin mirrors a unique physical object, process, organisation, person or other abstraction and can be used to answer what-if questions, present insights in an intuitive way and provide a way to interact with the physical object/ twin.
The key elements in a Digital Twin:
While there are many different views of what a digital twin is and is not, the following more or less lists the common set of characteristics that is present in nearly every digital twin: -

Connectivity created by IoT sensors on the physical product to obtain data and integrate through various technologies. Alternatively, capture on field information of assets through drone photography or LIDAR scans followed by 3D reconstruction using different techniques.

Digital Thread, a key enabler interconnecting all relevant systems and functional processes Homogenisation: decouples the information from its physical form

Re-programmable and smart, enabling a physical product to be reprogrammable manually and in an automatic manner

Digital traces and modularity, to diagnose where the problem occurred

Digital Twin, is not a single technology play, rather it is realized through an amalgamation of a multiple of technologies and essentially it consists of functional building blocks that address specific business aspects: -

Sensors and Assets capable of transmitting telemetry/data/ real-time data ingestion gathered from physical asset/ objects related to state, conditions and events

Connectivity between platform and sensors (Internet, 3G/4G, CDMA, LoRa, ...)

Data Platform core system for a) data management - To integrate, persist, transform and govern the data collected; b) analytics - Using machine learning framework and analytics to make real- time decision based on historical and streaming data; c) user experiences - combines the data and insights to present, advise and interact with the user or other machines

Digital Twin core capabilities that uses the managed data obtained by the Data Platform to create Applications for the Use Cases. Creates a digital thread based on semantic model, data dictionary and knowledge graph

Monitor applications for the operational team maintaining the Digital Twin solution

Enterprise systems, for authentication, security, libraries, utilities etc. reused by the platform

Use cases that enable the value obtained from the Digital Twin, these Use Cases would require either processes or combinations of the different functional components

Additionally the following blocks supports the underlying digital twin platform: -

Workflow and APIs: Extract and share data from multiple sources in creating the digital twin and/ or infuses the insights within workflow of digital twin

Infrastructure: Hybrid infrastructure including Cloud, Edge compute, In-plant infrastructure, Network (IT/OT) etc., OT infrastructure etc.

Figure 2: Digital Twin functional blocks The Digital Architecture of Digital Twin:
The logical digital architecture for digital twin is the level 2 details from what has been described in the above section. Objective is to be able to support the functionality to connect, monitor, predict and simulate multiple physical objects, assets and/ or processes.
Figure 3: Digital Twin Logical Architecture Building Digital Twin with Azure and hybrid technology stack:
We propose here a digital twin that is primarily based on Azure stack along with the other software: -
Figure 4: Digital Twin Technology Architecture with Azure and hybrid software platform

Architecture Layer: Data Platform: Ingestion, Normalisation, Persistence, Management, Integration, AI/ ML/ Analytics, Microservices

Technology: IoT Hub, Event Hub, PostGreSQL/ SQL DB, Cosmos DB, Azure Time Series Insights, Databricks, Data Factory, Azure ML, Azure DevOps, Synapse

Vendor: Azure

Purpose: Ingesting and processing device telemetry securely is one of the key requirements in Digital twins. A combination of IoT Hub and Event Hub will allow connecting to heterogenous data sources, multiple protocol and support streaming ingestion. Databricks and Data Factory meant to provide consistency of data through the validation, enrichment, cataloguing and transformation conforming to the standard and integrate with the other systems. Considering the diverse nature of data that will be handled by Digital Twin, polyglot storage is recommended. Thus a combination of relational, non-relational, time-series, data lake and warehouse is required. Cloud based Machine Learning Platform for building, training and deploying models based on the data collected via data platform. Also provides ability to perform analytics on streaming data.

Architecture Layer: Digital Twin Framework: Digital Twin Engine, Digital Thread

Technology: Azure Digital Twin Service, KITT

Vendor: Azure, IBM

Purpose: The Knowledge Graph represents a collection of interlinked descriptions of entities - objects, events or concepts. It will put data in context via linking and semantic metadata. Azure Digital Twin is a platform that enable creating a digital representation of real-world things, places, business processes and people. It is based on open modelling language to create custom domain models of any connected environment using Digital Twins Definition Language (DTDL). The Live execution environment brings digital twins to life in a live graph representation. Input from IoT and business systems to connect assets, including IoT devices, using Azure IoT Hub, Logic Apps and REST APIs. Output to Time Series Insights, storage and analytics using event routes to downstream services including Azure Synapse Analytics. The IBM asset KITT is a general purpose knowledge graph that enables the Digital Thread required to link lifecycle information and data together. KITT is proposed to be deployed on Red Hat OpenShift.

Architecture Layer: Digital Twin Solutions: Visualisation, Consumption, Intelligent Workflows, Intelligent Operations, Assets and Simulation

Technology: Unity, Reflect, Hololens, Spatial Anchor, Remote Rendering, RedHat Process Automation Manager, Logic Apps, IBM Maximo, OpenShift

Vendor: Azure, Unity, Redhat, IBM

Purpose: This layer is responsible for portal, real-time dashboards and command centres. AR and VR services are required to visualise diagnostics, predictions and recommendations for physical world. An extension of dashboard visualisation is also required in digital twin to provide a view in 3D/2D. Workflow Management in digital twin is intended to deal with the business processes, simulation and event based flows. Besides the Azure Logic Apps we also propose RedHat Process Automation which could be hosted in the RHOS on Azure. To provide secured access to application APIs and batch files we propose micro-service based applications built using AWS API Gateway, Node JS/ SpringBoot and exposed via API Gateway.

Architecture Layer: Governance & Operations: DataOps

Technology: Azure Databricks, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS)

Vendor: Azure

Purpose: DataOps and Data Governance is an essential element of Digital Twin that sits atop the big data which must be available on time, be automated and managed well to extract value. Azure Purview with Data Bricks provide end-end data capability to discover, prepare, combine and goven data for analytics, machine learning is the right fit for the purpose ADF for data orchestration, Azure databricks for cleansing and standardisation, ADLS for storage.

Architecture Layer: Operational Processes

Technology: MLOps, DevOps,

Vendor: Azure

Purpose: Azure MLOps and DevOps helps to build a continuous integration or continuous delivery workflow and fulfils the AI@Scale goals providing capability to build, train, deploy and maintain machine learning models in production reliably and efficiently.

Architecture Layer: Edge Services, Fog Services, Device Connectivity, Reality Data, Reconstruction and Modelling

Technology: Azure Edge, CISCO, Bentley, Perspective, Siemens, Dassault, Boston Dynamics, Precision Hawk..

Vendor: Misc.

Purpose: Digital Twin infrastructure transcends beyond cloud and on-premises infrastructure. We propose a miscellaneous solution including Azure edge, drone infra, robotics to cover the entire gamut of data sources such as reality data, modelling data etc.

Conclusion:
Digital Twin connects the digital and physical world as it truly takes the connected solutions to the next level with IoT, machine learning, robotics and virtual reality at its foundation. Creating an end-to-end digital twin platform, requires lot more than single set of capabilities with heterogenous software and hardware stack, multiple set of architecture with the principal theme being data. There are specialised software vendors for each layer or architecture, the flexibility comes from adopting a hybrid approach wherein the hyperscalers forms the core part of the solution. While the individual customer environment will determine hyperscalers, the advantage of Azure with its strong IoT and one of its kind Digital Twin centric platform can be leveraged to build powerful digital twin solutions.

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Building the digital representation with Digital Twin using Microsoft stack

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Sujay Nandi, Associate Partner and Executive IT Architect, Data and Technology Transformation at IBM Consulting Sanjay Panikkar, Lead IoT Architect and Consultant, Data and Technology Transformation...

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A digital twin is a digital replica of a living or non-living physical entity. By combining the physical and the virtual world, data is provided enabling the virtual entity to exist at the same time with the physical entity.

Specifically, a digital twin digitally replicates physical assets that can be used for various purposes. This digital representation provides the elements and the dynamics of how an Internet of Things (IoT) device operates and lives throughout its life cycle.

The fact that these processes are presented digitally, means that there is no need to arrange for a physical test cycle.

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There are options for real time execution or simulation in free mode (as fast as the hardware allows). During simulation, the user can observe simulation variables, manipulate these and visualise the results in charts. A scenario management feature allows change of the simulation variables automatically based on a scenario file. It is also possible to log to file the simulation variable values of all models.

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Containers in the Vehicle World — Fad or a Necessity?

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Containers in the Vehicle World — Fad or a Necessity?

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Containerisation is a major trend that is helping developers create and deploy applications faster. It enables higher portability, flexibility and brings applications closer to the desire state of “written once and run anywhere.” It is ideal for running on edge layer because of its low footprint and ability to interact with the cloud as well as the legacy services and its flexibility to run on multiple hardware.

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Containers in the Vehicle World — Fad or a Necessity?

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Sujay Nandi, Associate Partner and Executive IT Architect (IoT, Data and Automotive), Data and Technology Transformation @ IBM Consulting

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Control and troubleshoot heterogeneous AMR fleets with a click of a button

Work with robots and not as a robot – choose between full task automation, ad hoc task, or a combination of both.

Full visibility & control over a whole fleet up to a single AMR

Optimized efficiency through data-driven
task management

Cyber-secured operation

Schedule tasks, define ad hoc tasks, get a picture of your fleet’s status, summon robots, assist robots in need or analyze performance KPIs – all from intuitive role-based dashboards.

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MOV.AI for AMR site managers | enjoy uniterrupted operation

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Enjoy uninterrupted AMR operation - easily control heterogeneous robot fleets safely and securely with real-time Robotic Fleet Dashboards

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Robot on-board storage and processing power is limited. Offloading analysis and decision processes to edge or cloud-based systems promotes higher processing speeds and more functionality. Battery consumption also decreases, extending range. To address these issues, TEPUK developed a digital architecture that promotes universal connectivity with robots, mobile devices, or Internet of Things (IoT) sensor platforms. The architecture reviews digital communication quality, data criticality, file size, and virtual machine processing costs to decide whether to process data in batch mode or real time.

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The ARGOS challenge proved that wireless robot performance directly depends on the quality of communication to interfacing remote digital architecture. An early 10-day offshore test in high humidity and temperature environments resulted in 25% robot downtime from communication and hardware failures, with another 10% downtime due to extreme weather conditions. High-quality wireless communication is therefore critical with bandwidth and latency defining real-time functionality. TotalEnergies handles robot communication through 4G or 5G LTE protocols. Other systems use Wi-Fi or radio frequency, the latter considered the most robust by Cognite AS who is working on robotic systems for Aker BP.

Robot supervision

Robot on-board storage and processing power is limited. Offloading analysis and decision processes to edge or cloud-based systems promotes higher processing speeds and more functionality. Battery consumption also decreases, extending range. To address these issues, TEPUK developed a digital architecture that promotes universal connectivity with robots, mobile devices, or Internet of Things (IoT) sensor platforms. The architecture reviews digital communication quality, data criticality, file size, and virtual machine processing costs to decide whether to process data in batch mode or real time.

The digital platform, called OpsSuperVision, consists of data processing, single-source truth reference, and device control and data consumption (Fig. 1). Application interfaces communicate between the layers.

The processing layer contains machine learning (ML) models, cloud data, and general management of data and models. Uploaded data from robots or devices are processed at this level. It interfaces with reference-layer digital twins and pushes processed results to the reference data area (data lake) for storage and later processing.

The reference layer includes a digital twin, mission routing databases, and the data lake. It is the central core of the operating system. The digital twin models physical assets and continuously updates to provide a single data reference point, or "source of truth," for operations. The mission-routing database stores details of functions that devices (robots, handhelds, etc.) perform, including location information for navigation and data collection. The data lake stores results from ML models. Combined, this layer provides a consistent method of accessing and using qualified historic asset information.

The control-and-consume layer manages planning, monitoring, and reporting for devices. End-user interfaces include mission planning applications, mission summaries, and model prediction dashboards. Device missions are planned and sent to the device remotely using the mission planning application which interfaces with the digital twin and mission routing database in the reference layer. The mission-summary dashboard provides onboard robot-health monitoring including failures and safety-related issues in real-time or post-mission. The model-prediction dashboard provides operator review of robot and device sensors and ML-model results pulled from the data lake.

Application program interfaces (APIs) connect devices, components, and layers together. Fleet management APIs call actions for the robot, providing at minimum a method for pushing single missions to the device and providing ongoing telemetry for device location and status. The fleet management API is limited to coordinates or points of interest. Supervisor API combines digital-twin data with operator requests to allow third-party data collection systems and devices to perform data-collection missions. The digital twin provides location information, used by the fleet management API for navigation, and the supervisor API provides context for the mission with function requirements for inspection and operation.

A supervision API uploads data to storage in the processing layer. The API is also responsible for triggering real-time batch processing of sensor data through the ML models and transferring device data from cloud storage to the data lake. A quantum ML API retrieves information from the digital twin and identifies locations in the data lake for ML results and device mission data.

TotalEnergies created a new "Operation Room" function to interface robot activities with the off-site control room (Fig. 2). The operation room is adjacent to the control room and enables supervision and coordination of all remote mobile systems (unmanned aerial vehicles, ground-based robots, underwater robotic remotely operated vehicles, etc.). Operation room personnel oversee the fleet management system (FMS) in charge of sequencing robot and drone activities. Other duties include robot control for complex non-autonomous tasks, maintenance and repair of the FMS, and maintenance and repair of the robots.

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Work-class robots are being used offshore following the autonomous robots for gas and oil sites (ARGOS) robotics competition.

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TotalEnergies adopts robot fleet management to automate operations 2023

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TotalEnergies adopts robot fleet management to automate operations 2023

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A partnership between Rockwell and TotalEnergies will make use of IoT, gamification and digital twin technologies to drive autonomous operations for offshore platforms.

Rockwell Automation, which develops industrial automation and digital transformation tech, announced the partnership with energy giant TotalEnergies to implement a robot fleet management system, aiming to implement autonomous operations for its offshore platforms.

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A partnership between Rockwell and TotalEnergies will make use of IoT, gamification and digital twin technologies to drive autonomous operations for offshore platforms.
Rockwell Automation, which develops industrial automation and digital transformation tech, announced the partnership with energy giant TotalEnergies to implement a robot fleet management system, aiming to implement autonomous operations for its offshore platforms.

The long-running project will reach a significant milestone with its first test on an offshore asset scheduled for mid-2023.

The partners state the importance of robotic and autonomous operations for their operations, as well as for wind offshore projects, in enabling unmanned operations for long periods, reducing employee exposure to hazardous situations, increasing safety, attracting young talent interested in new technologies and further reducing CAPEX and OPEX.
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"Because of the remote and often harsh environments in which oil and gas companies operate offshore, there is a strategic objective to minimise employee exposure on these platforms," said Matt Graves, director at Kalypso, a Rockwell Automation company.

"Over the years, this has been achieved by improving the design and automating equipment. But there are still tasks that need to be performed manually, many of which involve observations by operators. For five years, TotalEnergies has been investigating the use of ground robots to undertake some of these manual tasks and the next step was to develop a control system to operate these robots remotely. For that, they turned to Kalypso."
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Gamifying automated operations

TotalEnergies has been working with Kalypso, a digital transformation-focused firm, and other partners to implement a Robotic Supervision System (RSS), aiming to allow operators located in an onshore control room to remotely supervise and coordinate the robots using IoT tech.

These robots autonomously perform the various activities that field operators are executing on conventional facilities: from periodic inspection operations and maintenance tasks to emergency response.

Challenged with how to interface the robots with existing industrial systems and how to represent the data in a user-friendly interface, Kalypso employed the Unity game engine, from Unity Technologies.

According to Kalypso, this real-time development platform and ecosystem forms the backbone of many of today's top video games. In recent years, industry has adopted it to create interactive digital content from 3D data and deploy it to various platforms, such as mobile devices, computers and AR and VR devices. This solution combines the functionality of a digital twin and the mobility and synchronisation of a gaming platform.

The resulting RSS concentrates the information provided by several different types of robots and consolidates the Human-Machine Interface (HMI) displays necessary for the remote operators to work efficiently and effectively.

"These tests are important at this stage of the project so that we understand all the operational aspects of using the robots for inspection purposes, anticipating further potential for maintenance and operation," Grégoire Audouin, R&D department robotics system architect at TotalEnergies, said.

"The main benefit for the operators is to remotely control these robots and have an immersive view from a central control room. There is huge potential for innovation in our industry."

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TotalEnergies adopts robot fleet management to automate operations

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Rockwell and TotalEnergies will use IoT, gamification and digital twin technologies to drive autonomous operations for offshore platforms.

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Kalypso employed the Unity game engine, from Unity Technologies, to overcome this challenge. This real-time development platform and robust ecosystem forms the backbone of many of today’s top video games.

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TotalEnergies to test remotely controlled robots on offshore platforms

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Rockwell subsidiary Kalypso has developed technology to command robotics on unmanned offshore platforms

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Digital Transformation, a long way to go. Where are we now and which opportunities are ahead of us?

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Digital Transformation, a long way to go. Where are we now and which opportunities are ahead of us?

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Guide to Digital Transformation Technologies and Their Business Impact

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Guide to Digital Transformation Technologies and Their Business Impact

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Digital transformation is changing a company's operations to make them more effective using digital technologies. The goal is to use technology to augment a current service rather than simply re-creating it in a digital format. Companies that successfully adopt digital transformation expand more quickly than their competitors. However, depending on certain company features, this method will seem different in each unique situation.

Technology is one aspect of the digital transformation framework. Changes in company culture and business operations are equally important to the organization's success. Large, successful companies that are going digital transformation may compete with more agile and digital-only competitors. At the same time, smaller firms can adjust their product offerings to changing market conditions.

This further proves that firms have the incorrect assumption that all technologies apply to all types of enterprises. Instead, the adoption of new technologies mostly depends on the requirements of an organization, its customer base, and market trends.

"According to Statista, spending on digital transformation technology and services is expected to exceed USD 1.8 trillion in 2022 and reach USD 2.8 trillion by 2025. This expansion reveals how much money companies want to spend on capital to remain competitive. According to Markets and Markets, global spending on digital technologies is predicted to reach USD 1247.5 billion by 2026."

The amount of money expended by digital transformation service providers for firms has increased dramatically. Organizations have switched to new business models to improve flexibility, scalability, and cost management. All services, such as supply chain management, online purchasing, and remote learning, are going digital.

No particular technology is at the center of the digital transition. Any technological advancement that helps a company to grow and produce better results might be included. A company's understanding of digital transformation (DT) principles and methodologies should be clear before they embark on its digital transformation. Only then, the corporate transformation performance will have a favorable effect.

This blog will explore the details of digital transformation, types of digital transformation, technologies, strategies, and benefits. So, let's have a look at it.
Digitally Transform Your Business
What is Digital Transformation?

Digital transformation fundamentally changes how a business function, communicates, and interacts with customers. The shift toward more digital operations disrupts the "conventional" manner of doing things. Therefore, promoting a digital culture within your firm and upskilling your workforce is essential. Because process transformations require a team effort. It's a cultural shift that involves constant experimentation and comfort with failure on the part of organizations.

The road to digital transformation services can take many different directions, and each organization's journey will be different. For instance, a business might use cloud computing or AI to improve the client experience. It might also revamp its supply chain to better use machine learning insights. Even then, business transformation services can accurately estimate and meet the goods consumers desire in a few months.

Differences Between Digitization, Digitalization, and Digital Transformation?

When discussing businesses and technology, there are many terms that might easily be misunderstood. Digitalization, digitization, and digital transformation framework are the most often used ones. To see the differences, let's examine each of them.

1) Digitization

Making anything digital or producing it in a digital format is referred to as digitization. For instance, if you publish a printed newsletter or magazine online. Or else if you sign papers online using an electronic signature.

2) Digitalization

Digitalization is using technology to alter your business model or create a new source of income. The goal is to establish digital business transformation services using online technology and channels. Instances such as automation speed up workflows or cloud computing to store data.

3) Digital Transformation

Digital transformation is a reinvention process. It examines how to use digital technology and procedures to create new systems, develop a digital mindset, and take advantage of untapped opportunities.
Useful link: 10 Factors That Can Drive Your 'Digital Transformation' Initiatives!
Digital Transformation Types

Although many firms concentrate on organizational change, there are four forms of digital transformation companies to go through if you want to get the most out of it. These consist of the following:

1) Business Model Transformation

Business model transformation is all about making basic adjustments to a company's operations, such as employees, operational methods, and tools. Consider Netflix, the industry titan that entirely flipped the traditional video distribution business model to disrupt it.

2) Process Transformation

This focuses on your internal systems, such as data, analytics, AI, and other systems that can help the company cut costs and improve operational effectiveness. For instance, with its recent Walgreens app revamp to serve better customers and centralize its digital assets. Healthcare retail giant Walgreens serves as an excellent illustration of this.

3) Organizational Transformation

Mindsets, procedures, capabilities, and skills need to redefine for a digital world. It improves advancing digital business transformation services through expansion projects that are founded in a new culture and style of thinking. Pitney Bowes is a fantastic example of this because it changed from providing mailing solutions to providing shipping and e-commerce technology before becoming a digital corporation.

4) Domain Transformation

This region presents a great opportunity to acquire new tools and enter a new industry. For instance, consider Google and the several commercial ventures it has launched, including Google Nest, an Internet of Things (IoT) product that provides thermostats and smoke detectors for the house.

Top Digital Transformation Technologies

Solutions for digital transformation using emerging technologies are picked based on an analysis of customer behavior, preferences, and unique internal business procedures. What technologies enable digital transformation are listed below. Let's go through it.

1) Artificial Intelligence and Machine Learning

The goal of machine learning (ML) and artificial intelligence (AI) is to simulate human cognitive operations. AI is used in speech recognition, natural language processing, computer vision, expert systems, and predictive analytics.

Initiatives for digital transformation companies heavily depend on AI/ML as part of new business strategies. These tools are essential for enhancing productivity as well as for making better use of the data that companies gather. Businesses may build creative ideas and better products and services by gaining actionable insights from data on digital transformation trends.

2) Cloud Technology

Cloud tools could significantly change existing business models. Using them enables the flexible usage of remote resources for on-demand data processing and storage. And that significantly lowers the cost of the infrastructure and hardware. With the help of this technology, teams may operate online more effectively and store massive volumes of data. While still preserving the highest level of security.

The financial gain for firms is another significant benefit of using cloud tools. After all, the first few years after the purchase are when in-house hardware purchases are more profitable in digital transformation tools.

3) Big Data

Data is a crucial resource for most enterprises and is referred to as the "fuel" of the modern economy. This has resulted in exponential expansion, both a challenge and an opportunity for any firm. This growth anticipates continuing in the upcoming years.

Big data can consist of structured, semi-structured, and unstructured information gathered by firms from their clients, during routine business activities, or from outside sources. Predictive modeling, data mining, and other data analytics techniques can all be applied to this data.

4) Real-Time Analytics

Analyzing related resources and data as soon as they enter a system is known as real-time analytics. Real-time computing refers to the capacity to respond to data in a manner that users perceive as quick.

Real-time data delivery from operational systems is made possible by streaming data architectures. Which also make use of powerful analytics engines and enable quick operational decisions. Robotic process automation (RPA) and other types of automated policy enforcement can execute these choices in digital transformation trends.

5) IoT and 5G

The Internet of Things (IoT) is a combination of computers, machines, and other items linked to the Internet. And it has the capability to send and receive data through a network. They frequently can operate without supervision from a person or traditional computer system in digital transformation tools.

IoT devices need more capacity, higher transmission speeds, and seamless communications, which 5G technology enables. For instance, as part of their digital transformation trends, most of the world's big cities have established an IoT sensor network, with many of them linked by 5G.

The digital revolution in the manufacturing area is being driven by the Industrial Internet of Things (IIoT), often known as Industry 4.0. With this technology, firms may enhance workflows and boost flexibility, innovation, speed, and quality.
Useful link: 9 Key Digital Transformation Trends 'To Watch' in 2020 and Further
How to Adopt a Successful Digital Transformation Strategy?

A strategy for digital transformation cloud is a course of action for starting and advancing a digital transformation in the future for the industry. What business aims and objectives you hope to perform through digital transformation challenges will be specified in your strategy.
Here are a few steps to think about when executing a digital transformation platform strategy:
1) Establish New Business Processes

Your "business as usual" plan might not align with your digital IT transformation plan. Your firm will only succeed if you develop and implement new processes.

A digital transformation plan may necessitate some firms' thorough revamp of operations. To effectively manage this change, all parties, such as employees and other stakeholders, must be ensured. You should be aware of the updates, who is responsible for what, and what mechanisms are being used to support them.

2) Determine Your Aims and Objectives

Your objectives should be laid out in a digital transformation strategy, along with the steps required to meet them. Every firm experience digital IT transformation in a different way. Thus, it's crucial to remember that every organization has different goals. But there are several fundamental goals that each business should consider:

How can you boost client engagement?

With the implementation of new tools and methods, is it possible to develop a more economical and practical company model?

Do you have methods in place for gathering information and data from analytics?

By providing answers to these questions, you may decide which elements of your strategy should be addressed first and which parts of your plan need immediate attention.

3) Get Employees and Leaders on Board

You need people's support if you want your digital transformation plan to be successful. Obtaining executive sponsorship for your activities is the first stage. It is simple to start the planning process for digital transformation when there is executive support. In addition, having the C-suite on board helps hasten your digital transformation market.

Pay attention to the issues raised by your team members and employees. They will be more ready to participate in your transformation process if you can use digital transformation companies to address their challenges. Ensure that your staff members know the enterprise digital transformation platform and how it affects your business. Additionally, you can arrange conferences with significant parties to review the DX procedure and identify any problems before you start.

4) Create KPIs

The next stage is to create KPIs to monitor goals and measure success. Start with goals that are important to your team. For instance, IT teams can start keeping track of KPIs for a specific kind of infrastructure. Monitoring business activity trends and volumes might be the first step for service delivery and assurance teams. KPIs provide you with a target to work toward and will help assess your efforts' effectiveness.

To evaluate the success of your KPIs, you can also include the best-case scenario, the worst-case scenario, and your anticipated outcome.

5) Pick Your Technologies Carefully

Make sure the technology you choose is compatible with the processes you are optimizing. Locate a technology that satisfies your requirements and aids in business expansion. In the end, the technology you choose should support your aims and be in line with your ambitions.
Useful link: Drive Customer Experience With Digital Transformation
Digital Transformation Benefits
The following are just a few advantages of digital transformation companies and their workforce:
1) Enables the Monetization of Software

When the annual Microsoft Convergence conference was taking place in 2015, Satya Nadella, the company's CEO, turned to face the room's leaders in business and industry and famously said: "Every company is a software company." However, they didn't understand software centricity well at the time.

All business leaders know that switching from a product-centric to a software-centric approach is essential. And that the best ROI for firms comes from software monetization. However, several firms fail to take off because they lack the knowledge to start software monetization engines.

2) Enables High-Quality User Experience

High-value firms are aware that they are providing experiences and products. Automaton, AI, and self-service tools are the foundation of digital transformation solutions. Which enables stunning, simple experiences. A smooth user experience will demonstrate that you have mastered the digital age.

3) Increase Customer Satisfaction

Expectations from customers have never been higher. On the one hand, clients desire tailored services that cater to their particular requirements. However, they don't want to interact with people when it comes to things like accessing, updating, or deactivating and reactivating software since they want things to happen automatically. You will be able to use powerful digital tools and strategies, one of the most apparent benefits of digitization for business.

4) Enhance Communication and Encourages Collaboration

You need a digital platform that promotes communication and collaboration between all internal divisions. Suppose you want to increase innovation and output. Digital transformation solutions get rid of redundant processes, long response times, lost data, and inefficient idea sharing. Digitalizing your company's internal communications will boost responsibility, creativity, and productivity. At the same time, you are giving the edge you need to exceed the competition.

5) Improve Operational Efficiency

Your working efficiency increases with digital transformation solutions. You can streamline cumbersome manual operations and cut costs by combining office systems, automating delivery methods, and updating your products. You can increase productivity and bridge income gaps using digital business process transformation. Since effective business practices are linked with digital business.

6) Increase Agility and Innovation

Agility in a company refers to the capacity to evolve swiftly and continually. Particularly, when it comes to digital operations. An agile organization is better able to manage uncertainty, establish responsibility, and accountability, reduce risk, and accomplish particular goals. This will assist you in building a successful and sustainable business.

Conclusion

Companies across all industries must adopt and adapt to digital to compete and flourish. However, navigating the digital shift to engage with customers and exert influence online can be challenging for many.

Implementation a single technology would not be sufficient to begin the digital transformation process. For all business operations, a technology-integrated approach is necessary. And not just within the company but also while dealing with its clients or partners.

Digitalization must eventually become a strategic cornerstone for every business and organization if they want to stay competitive and offer better services to their clients. Implementing digital transformation projects is wise if ease, scalability, and security are your main concerns.

Whether you need assistance along the way or wish to begin your enterprise digital transformation journey. Then, Veritis, the Stevie Award winner, will assist you in your efforts to implement digital transformation by guiding you through the process.
Got Questions? Schedule A Meeting Additional Resources:

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How Digital Transformation Technologies Help Your Business Grow

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Digital transformation technologies become the key enabler in your business transformation. Benefits of Successful Digital Transformation.

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See all projects in one platform - in real time

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See all projects in one platform - in real time

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The SDX-Compact makes it possible to equip any machine with the latest surveying technology within a few minutes. The unique plug-and-play principle means that the system can be quickly switched between machines and you can dispense with manual data acquisition. Because from now on, the SDX-Compact will take care of your complete documentation and recording of billing-relevant data directly outside on the construction site.

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Surveying with the construction machine! Automatically record all data for billing and documentation during the earthworks.

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A next generation solution that puts farmers in control. A simple way to manage and monitor your farm, no matter where you are.

https://www.robotics247.com/article/agtonomy_closes_5m_round_semi_autonomous_agricultural_equipment

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https://www.inorbit.ai/

Description

Developer of a cloud-based robotics management platform designed to support efficient robotic operations. The company's platform permits remote data collection, monitoring and control without the need for a virtual private network using industry-standard internet of things protocols to handle spotty connections and provides source code access for inspection of any robot-side code and its technology includes adaptive diagnostics and predictive analytics, enabling robotics companies and operators to develop, deploy and operate smart robots at a global scale.

https://pitchbook.com/profiles/company/264404-26#overview

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With our universal fleet management system, we help manage diverse mobile robot fleets effortlessly

WITH SIMPLE, FAST, AND SECURE INTEGRATION.

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About: Vision, Facts, Culture & Employees | Meili Robots

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We're a team of technologists, creative problem solvers, and business thinkers seeking to orchestrate the chaos in the mobile robot industry.

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FORMANT: The data platform for robotics companies

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FORMANT: The data platform for robotics companies

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The data platform for robotics companies

Formant is a cloud platform that helps robotics companies easily deploy, scale, and manage their fleets.

Get industry-leading solutions for teleoperation, fleet management, device monitoring, and more.

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You can integrate your data, visualise asset models, navigate the model, collaborate with all stakeholders and orchestrate all processes in one place. As a result, ground truth becomes available to all in real time.

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The journey with Aize often starts with a highly accurate digital 3D model of your as-designed or as-built asset. Aize can digitally visualise your asset once you provide the parameters, dimensions, and properties needed. Isolate equipment, systems and areas to help you focus on what is relevant to your expertise.

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Altair’s one total twin solution empowers organizations to transform their products, systems, and processes. With features that combine leading simulation, high-performance computing (HPC), artificial intelligence (AI), data analytics, and Internet of Things (IoT) capabilities, teams can design, build, test, optimize, evaluate what-if scenarios, perform predictive maintenance, and extend the remaining useful life (RUL) of their products—without the need of physical prototypes.

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Altair's one total twin solution empowers organizations to transform their products, systems, and processes. With features that combine leading simulation, high-performance computing (HPC), artificial intelligence (AI), data analytics, and Internet of Things (IoT) capabilities, teams can design, build, test, optimize, evaluate what-if scenarios, perform predictive maintenance, and extend the remaining useful life (RUL) of their products-without the need of physical prototypes.

Altair's flexible, connected capabilities and smart product development solutions also enable comprehensive cross-functional system evaluation, which eliminates information silos and communication bottlenecks during product development. With these capabilities, organizations become more efficient and can deploy digital twin technology when and where they need it - through any or all lifecycle stages - from pre-production conceptual design through in-service performance.

A comprehensive, detailed, international report on the present and future of digital twin technology that examines how digital twin is understood, how it's used, why it's used, who's using it, and more.

Download the Report

Pre-Production Twins

Design Concept

In the pre-production stage, organizations can deploy the as-specified twin, which covers specifications and requirements, development, and simulation. These twins help teams design, analyze, and optimize performance in the earliest stages of the system lifecycle without requiring expensive prototypes.

Detailed Design

As system concepts mature into detailed designs, organizations can deploy the as-designed twin for validation studies, real-world performance prediction, and streamlined mechatronic product development. Teams can also converge multiphysics simulation with advanced HPC, AI, and data analytics capabilities in a unified, cohesive environment.

Products for pre-production include Altair® Twin Activate™, Altair® Inspire™, Altair Drive, Altair® HyperWorks®, Altair® PollEx™, Altair® Flux®, Altair Compose®, Altair® Feko®, Altair® PSIM™, Altair® EEvision™, XLDyn (via the Altair Partner Alliance), and Altair consulting services.

Post-Production Twins

Built Systems

For systems that have reached the production stage, the as-built twin helps teams evaluate advanced virtual system dynamics under what-if scenarios, deploy reduced order modeling (ROM), detect design sensitivities, and resolve test failures. Organizations benefit from capabilities that enable mixed-reality simulations that lead to optimal designs - especially concerning very large structures or situations that are otherwise impossible to evaluate in the real world. Teams can also resolve test failures with multibody and controls simulation, and real-time visualization.

Integrated Devices of Built Systems

Organizations can use the as-manufactured twin to evaluate integrated software, processors, and hardware involved with system controls, such as human-driver, ergonomics, immersion, and virtual reality. Teams can simulate realistic and unexpected events, improve workability and operation windows, and produce high-fidelity displays of innovations in interactive, realistic environments.

Products for post-production include Altair Embed®, Altair® MotionSolve®, Altair® HyperStudy®, Altair® Panopticon™, Design Explorer inside of Altair® DesignAI™, and Altair consulting services.

See examples of digital twins for systems in pre- and post-production.

System-In-Service Twins

The as-sustained twin handles predictive analytics and maintenance of systems that are in service. Teams can leverage real-time data stream analytics and machine learning  to optimize system performance, deliver ideal maintenance routines, trigger insights based on anomaly detection, determine a system's RUL, and more. This capability delivers fast, real-time insights about system status, which helps organizations make optimal operational adjustments to maximize system life and avoid failures.

The Altair® RapidMiner® platform houses the tools users need for systems-in-service, including Altair® IoT Studio™, Altair SLC™, Altair® Monarch®, Altair® Knowledge Studio®, in addition to Altair's consulting services.

See examples of digital twins for systems in service.
Learn how Leonardo uses Altair digital twins.

Watch the Video

Flexible, Open, and Connected Platform

At the core of our  digital twin integration platform are our flexible, agile, and vendor-agnostic software capabilities for executing twins in production and connecting them to real-world data  in real-time. This platform provides the essential building blocks for digital twin developers from various specialties to get started fast, scale efficiently, and streamline changes as systems evolve over time.

Learn how our platform and One Total Twin™ solution are helping numerous industries like yours:

Architecture, engineering, and construction (AEC)

Automotive

Aerospace and defense

Banking, financial services, and insurance (BFSI)

Consumer goods

Energy

Healthcare

Heavy equipment

High-tech

Infrastructure

Life and earth sciences

Materials

See examples of digital twin integration.

Contact Us

Make Better Product Decisions

Deploying a digital twin means you can make stronger, data-driven decisions about your product's future. The detailed and in-depth information a digital twin provides empowers you to convert empirical insights to action, improving customer satisfaction through increased product reliability and improved performance. Altair provides you with the digital twin building blocks that allow you to connect disparate development disciplines and enable simulation-driven teamwork.

Electrical engineers, controls specialists, system engineers, structural designers, dynamics specialists, manufacturing experts, software developers and data scientists are provided with a new way to collaborate and gain holistic system understanding. Altair helps you understand how your product truly behaves in the real-world so you can make better decisions for your product's future.

Validate Your Product Quickly and Reliably

Digital twins are especially powerful for product validation when physical prototype validation is unrealistic. Sometimes prototypes are too expensive, or operate in difficult to replicate environments, or require human intervention. In these scenarios, using a digital twin instead of a physical twin can help you understand your product's behavior for substantially less investment.

Additionally, digital twins can be subjected to many more experiments at much higher frequencies. They are the cost-effective, safe, and accurate way of testing your hypotheses before committing to print for manufacturing, patent for prosthetics, grid for racing, or go for launch.

Improve Asset Performance and Efficiency

In production, digital twins improve your asset's performance, efficiency and remaining useful life. They are a digital window into your asset's operation, applying physics and machine learning in real time so you can gain otherwise inscrutable information into behavior then translate it directly to action. This reduces the cost of operation, avoids production stoppages from catastrophic failures, and extends the working life of individual assets.

The Altair digital twin integration platform is the only solution that gives you a window to address the full complexity of your asset's operation - machine learning insights blended with physics simulation - to help you find hidden inefficiencies and correct them.

Get the Whole Picture

While digital twins' usefulness is unquestioned, their effective implementation can be difficult - every problem to be addressed with a digital twin needs a different approach to find the optimal solution. Altair addresses this complexity through a unique blend of physical simulation methods, data analytics, and machine learning techniques to provide a complete picture of the status of a product in the real world. Our approach can help you add virtual sensors where physical sensors are impossible, intuit maintenance needs ahead of catastrophic breakdowns, and optimize test rig performance - all within one ecosystem.

At any stage in your system lifecycle and through all levels of complexity, Altair can solve your most difficult problems with our one total digital twin solution.

Read Our Blog Posts

Get in Touch

We'd love to hear from you. Here's how you can reach us.

Contact Us

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Digital Twin Platform for Optimized Product Performance | Altair

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Optimize product performance and life with Altair's digital twin technology that is both physics-driven and data-driven. Make better product decisions and validate your product quickly and reliably.

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About

Contoro Robotics combines AI and human intelligence with teleoperation.

Funding

Contoro Robotics has raised a total of $8.5M in funding over 2 rounds. Their latest funding was raised on May 26, 2023 from a Seed round.Contoro Robotics is funded by 7 investors. Kakao Ventures and The University of Texas at Austin are the most recent investors.

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ST. JOHN’S, NEWFOUNDLAND, June 28, 2018 /GLOBE NEWSWIRE/ — Kraken Robotics Inc. (TSX-V: PNG, OTCQB: KRKNF) is pleased to announce that the non-brokered private placement offering (the “Offering“) announced on June 20, 2018 closed today for aggregate gross proceeds of $2.3 million.

“Kraken is very pleased to have completed this financing with our customer Ocean Infinity,” said Karl Kenny, Kraken’s President and CEO. “The financing strengthens our balance sheet with a patient investor and supportive customer and validates our strategic efforts to build a vertically integrated offering of sensors, software and systems for the underwater robotics market. We will continue to work with Ocean Infinity to help provide its customers an efficient, differentiated service offering, leveraging a variety of products and services developed by Kraken.”

Offering Details

The Offering was comprised of 11,520,000 units (the “Units“) at a purchase price of $0.20 per Unit for aggregate gross proceeds of $2,304,000. Each Unit consisted of one common share and one-half of one common share purchase warrant (each whole common share purchase warrant, a “Warrant“), with each Warrant exercisable to acquire one common share of Kraken at $0.40 for a period of 36 months from the date of issuance, subject to adjustment and acceleration. All proceeds raised from the sale of the Units will be used by Kraken to build inventory and general corporate and working capital purposes.

The securities issued pursuant to the Offering are subject to a four-month statutory hold period commencing from the closing date under applicable Canadian securities laws, in addition to such other restrictions as may apply under applicable securities laws of jurisdictions outside Canada. In addition, Ocean Infinity has agreed to an additional 32 month hold period resulting in a combined 36 month hold period.

The Warrants are subject to an acceleration clause whereby if the closing trading price of the common shares is greater than $0.50 for 20 consecutive trading days after the date that is four months and a day after the closing of the Offering, Kraken may, at its option, elect to accelerate the expiry date of the Warrants to 20 calendar days following the delivery of a written acceleration notice.

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SwarmGPT: Using LLMs to Control Drone Swarms

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SwarmGPT: Using LLMs to Control Drone Swarms

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A system that integrates large language models (LLMs) with safe swarm motion planning - offering an automated and novel approach to deployable drone swarm choreography. Swarm-GPT enables users to automatically generate synchronized drone performances through natural language instructions. With an emphasis on safety and creativity, Swarm-GPT integrates the creative power of generative models with the effectiveness and safety of model-based planning algorithms.

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SwarmGPT - Using LLMs to Control Drone Swarms - SwarmGPT - Learning Systems Lab

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A novel approach to choreographing the movements of drone swarms to music using an LLM and user inputs.

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SmarmLab: a versatile Matlab package for drone swarm simulation.

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SmarmLab: a versatile Matlab package for drone swarm simulation.

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SwarmLab is a drone swarm simulator written in Matlab. It aims at:

1. simulating single drones;

2. simulating swarms of drones;

This software is designed with versatility and scalability in mind. It allows for fast programming and easy incorporation of various modules designed for drone and drone swarm simulations. It also decreases the coding effort by offering built-in and ready-to-use functionalities. These features make this package suitable to different applications in the area of drones and swarm robotics, including fast algorithm development, training, education, and the automatic collection of simulated data.

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GitHub - lis-epfl/swarmlab: SmarmLab: a versatile Matlab package for drone swarm simulation.

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SmarmLab: a versatile Matlab package for drone swarm simulation. - lis-epfl/swarmlab

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Simulate mmWave radar based drone control i Gazebo with ROS2 and PX4

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Simulate mmWave radar based drone control i Gazebo with ROS2 and PX4

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Simulate mmWave radar based drone control in Gazebo with ROS2 and PX4

Prerequisites

Tested with:

Ubuntu 20.04.3 LTS

ROS2 Foxy

Gazebo 11.9.0

px4_ros_com commit 90538d841a383fe9631b7046096f9aa808a43121

px4_msgs commit 7f89976091235579633935b7ccaab68b2debbe19

PX4 Autopilot commit d7a962b4269d3ca3d2dcae44da7a37177af1d8cd

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GitHub - nhma20/mmWave_ROS2_PX4_Gazebo: Simulate mmWave radar based drone control i Gazebo with ROS2 and PX4

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Simulate mmWave radar based drone control i Gazebo with ROS2 and PX4 - nhma20/mmWave_ROS2_PX4_Gazebo

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How to spawn multiple USVs on VRX sim enter command "roslaunch vrx_multirobot.launch" after initializing roscore These scripts will open the sim environment with two USVs. vrx.launch file is the default launch file of the simulation environment. You can edit these folders by comparing your default launch file to these files.

robots.launch file has the parameters for spawning USV's one_robot.launch spawns one robot. vrx_multirobot.launch file calls this script for creating each robot.

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GitHub - MustafaBayrak1/spawn_multiple_robot: Code to spawn multiple USVs on VRX sim

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Code to spawn multiple USVs on VRX sim. Contribute to MustafaBayrak1/spawn_multiple_robot development by creating an account on GitHub.