NEC Develops AI Robot Control Technology For Safe Navigation In Obstacle-Rich Environments
August 28, 2025 by Mai Tao
NEC has developed technology that utilizes AI to enable safe, efficient autonomous control of robot movement even in complex environments with many obstacles.
NEC's in-house demonstrations of this technology have confirmed that a robot's travel time can be reduced by“up to 50 percent when compared to conventional methods”.
This new technology utilizes NEC's proprietary AI, which has been trained with the knowledge of multiple AIs, to generate optimal travel paths in real time. NEC aims to commercialize this technology by the end of fiscal 2026.
In recent years, automation through the introduction of robots has been progressing in large logistics warehouses and factories due to a decrease in labor forces and the need to improve productivity.
However, in existing small- and medium-sized logistics warehouses, where it is difficult to prepare a dedicated environment for robots, and in retail stores, where aisles are narrow and display shelves and products are obstacles, it is difficult to secure paths for robots to move, which has hindered their introduction.
Furthermore, in robot control technology, there has been a trade-off between the time required to predict a path and the quality of the estimated path, and it takes time to estimate optimal routes. Therefore, robot control technology has not been practical in complex environments with many obstacles.
Features of the robot control technology developed by NEC to address these issues include the following.
Proprietary AI that generates optimal routes in real timeTraditionally, autonomous robot navigation in environments with numerous obstacles has relied on a combination of AI technologies and methods that generate paths based on predefined rules and procedures. However, there have been challenges in achieving optimal path generation that balances safety and efficiency.
Additionally, while combining multiple AI systems can generate more appropriate paths, increasing the number of AI systems tends to prolong processing time and make real-time control more difficult.
NEC has developed a proprietary AI that can learn the paths generated by multiple AI systems and generate multiple paths at once. This enables the generation of safe and efficient optimal paths even in environments with irregularly placed obstacles, thereby realizing real-time robot control.
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