Abstract: Aiming at the problems of large randomness,slow convergence,and poor path quality of traditional RRT-Connect algorithm in path planning,a RRT-Connect robotic arm path planning algorithm based on improved APF guidance was proposed. Firstly,a dynamic bias strategy was introduced to reduce the problem of large randomness of the original RRT-Connect algorithm; secondly,when expanding a new node,the node randomness and the weight of the total potential field were adaptively adjusted according to the distance from the obstacle; then,a robotic arm collision detection model was incorporated and a two-way direct-connected linear interpolation detection was carried out until the initial path was generated; finally,three times of B-spline smoothing was carried out on the generated path to produce feasible paths that conform to the actual motion constraints of the robotic arm. 3 different environments were constructed in 2D and 3D to simulate and to compare with the improved algorithm,the results showed that the improved algorithm could effectively improve the relevant performance. The application of the improved algorithm to the physical platform further proves the effectiveness and feasibility of the algorithm.

Key words: robotic arm, path planning, RRT-Connect, artificial potential field