An Obstacle Avoiding Motion Planning Method for Manipulator using Progressive Dynamic Local Search

To enhance the efficiency of motion planning, we introduce a new angle profile searching method known as Progressive Dynamic Local Search (PDLS). Building upon a collision-free multi-segment path established by the RSPM-PS algorithm, PDLS methodically computes angle profiles from the initial to the target pose, focusing searches near each point's predecessor. It refines the path's smoothness by adding intermediate points and sets the local search radius through the Jacobian matrix, optimizing convergence. Our method also innovates in assessing angle profile quality, introducing a combined error function that judiciously weighs the importance of position and attitude accuracy. Furthermore, we mitigate sudden changes in joint acceleration by interpolating angle profiles using a quintic polynomial. Tests in MATLAB and on a JAKA Zu311 manipulator demonstrate PDLS's advantages: reduced run times, precise calculations, and improved convergence rates.