Potential Field-Based Online Path Planning for Robust Cable Routing

This paper tackles the complex task of routing elastic deformable linear objects (DLOs) characterized by considerable stiffness, such as cables or hoses, which are already constrained at both ends. Specifically, a single arm robot is controlled to slide along the unknown contour of the cable, performing collision-free contour following, and to insert specific DLO segments into intermediate known clips. The contour following motion is executed avoiding both collisions with static obstacles and excessive deformation of the manipulated DLO. In particular, the path is defined considering an artificial potential field that is updated after each sliding motion along the DLO. This field accounts for static obstacles, the local cable shape (reconstructed using tactile sensors on the gripper fingertips) and the estimation of the global DLO shape obtained from a dynamic model of the DLO, accounting for the constraints imposed by the clips and the gripper. The proposed method is experimentally validated on an industrial robot executing cable routing in several DLO configurations.