Path planning of a 5-dof robotic arm based on BiRRT-APF algorithm considering obstacle avoidance

In robotic applications, an efficient path planning in a prescribed environment is the central issue, which is a challenging task for multiple degree-of-freedom articulated robotic arms. In this light, the path planning for robotic manipulators based on the combined artificial potential field method and bidirectional rapidly exploring random tree (BiRRT-APF) algorithm is proposed in this paper, aiming to handle the problems of highly possible randomness and low search efficiency. In order to improve the attraction function to speed up the efficiency of searching path, the characteristics of the Bi-RRT algorithm (i.e., bi-directional growth of random trees), is integrated to reduce the search time. Subsequently, a path construction strategy is proposed to remove the redundant nodes of the path, for the increased smoothness of the path and reduced memory storages of the algorithm. The effectiveness of the proposed path planning algorithm is illustrated with a 5-dof robotic arm, and is verified with MATLAB TM and CoppeliaSim TM co-simulation, through a comparative study among different algorithms. The results show that the proposed BiRRT-APF algorithm can decrease the randomness of node growth and reduce the number of algorithm iterations, resulting in faster convergence of a smooth path for reduced computational burden.