Vision-guided active collision avoidance for human-robot collaborations

This paper reports a novel methodology of real-time active collision avoidance in an augmented environment, where virtual 3D models of robots and real camera images of operators are used for monitoring and collision detection. A prototype system is developed and linked to robot controllers for adaptive robot control, with zero robot programming for end users. According to the result of collision detection, the system can alert an operator, stop a robot, or modify the robot’s trajectory away from an approaching operator. Through a case study, it shows that this method can be applied to real-world applications such as human-robot collaborative assembly to safeguard human operators.