Human-robot shared control system based on 3D point cloud and teleoperation

Owing to the constraints of unstructured environments, it is difficult to ensure safe, accurate, and smooth completion of tasks using autonomous robots. Moreover, for small-batch and customized tasks, autonomous operation requires path planning for each task, thus reducing efficiency. We propose a human-robot shared control system based on a 3D point cloud and teleoperation for a robot to assist human operators in the performance of dangerous and cumbersome tasks. The system leverages the operator’s skills and experience to deal with emergencies and perform online error correction. In this framework, a depth camera acquires the 3D point cloud of the target object to automatically adjust the end-effector orientation. The operator controls the manipulator trajectory through a teleoperation device. The force exerted by the manipulator on the object is automatically adjusted by the robot, thus reducing the workload for the operator and improving the efficiency of task execution. In addition, hybrid force/motion control is used to decouple teleoperation from force control to ensure that force and position regulation will not interfere with each other. The proposed framework was validated using the ELITE robot to perform a force control scanning task.