Human error recovery for a human/robot parts conveyance system

The study concerns a human error recovery function for efficient human/robot collaborative parts conveyance tasks, which has not been discussed so far in construction of human/robot coexistence systems. We propose a human operational intention inference updater which allows a robot to judge whether the goal intended to reach by the operator is correct or not, from incomplete trajectory data sequence of the robot endtip maneuvered by the operator. Experimental results showed that a use of the proposed inference updater reduced the task execution time even when human error occurred in a task, which demonstrate the usefulness of the updater.