Pose Estimation and Collision Detection in Human-robot Coexistence

A method of pose estimation and collision detection in human-robot coexistence is proposed. Firstly, an optical three-dimensional motion capture system is used to obtain the pose information of mark points to establish a kinematic model of the human arm. Secondly, in order to solve the problem that the pose information of some mark points is lost due to obstacles in the workspace, the elbow joint angle obtained by the angle sensor is used as the input of the human arm kinematics model to obtain the pose information of the end of the human arm. Thirdly, the capsule model of the human arm and the collaborative robot is established, and the shortest distance among the capsules is calculated, so as to judge the relative pose relationship between the human and the machine and realize the collision detection. Finally, 10 persons are used to evaluate the human-machine pose estimation and collision detection methods in different human-machine coexistence scenarios. The experimental results show that the error of the end position of the human arm estimated by the proposed method is within 20mm, and the maximum error of the shortest distance between the human and the machine is 14.53mm, which is sufficient for man-machine collision detection.