My job isn't easy, the technology never stops. Every year, more autonomous robotic systems are developed. The robot's onboard computer has to be able to accurately interpret data from sensors and create routes. Also, it needs to be able to monitor its coordinates to navigate space. These processes require a great deal of computing power and are more accurate the more precise they are. Robots require computing power to process data from sensors and map-building, but also for other tasks that are crucial. It is difficult to find the power needed, particularly for robots with small sizes. This issue can be solved through the development of algorithmic and software that can be used to speed up video processing and analysis systems. It is a universal computing device that lets real-time image processing, the building of volumetric maps as well as volumetric data processing. It will run using parallel computing architectures (parallel computing architecture), and will employ the logic of algebra in addition to one of the SLAM algorithms.

SLAM (simultaneous mapping and localization) is a method for simultaneous mapping and localization. Applications of robots equipped with this system are extensive and range from strategically important tasks (forest fire prevention and rescue of people during emergency situations) to tasks that are social (robot guides and house helpers). We are open to collaboration with vendors and investors.