Human Motion Mapping to a Robot Arm with Redundancy Resolution

The problem of image based visual servoing for robots working in a dynamic environment is addressed in this paper. It is assumed that the environment is observed by depth sensors which allow to measure the distance between any moving obstacle and the robot. The main idea is to control suitable image moments during the interaction phase to relax a certain number of robot’s degrees of freedom. If an obstacle approaches the robot, the main visual servoing task is attenuated or completely abandoned while the image features are kept in the camera field of view by controlling the image moments. Fuzzy rules are used to set the reference values for the controller. Beside that, the relaxed redundancy of the robot is exploited to avoid collisions as well. After removing the risk of collision, the main visual servoing task is resumed. The effectiveness of the algorithm is shown by several case studies on a KUKA LWR 4 robot arm.