Robotic Arm Motion Planning for Obstacle Avoidance Based on the CMN-RRT * Method

Abstract

With the development of the robotic arm industry, the current industrial requirements for robotic arm motion planning are gradually increasing. The article uses the KINOVA JACO GEN2 robotic arm to study the obstacle avoidance path planning algorithm based on the Central Multi-Node (CMN) RRT* algorithm. The study is mainly aimed at the problems of long calculation time and poor obstacle avoidance effect of the traditional RRT* algorithm. The main improved method is to optimize the sampling method of the traditional algorithm. The idea of connect is introduced in the path growth process to make multiple trees grow at the same time and make the obstacle avoidance process faster. Finally, the experimental results show that the CMN-RRT* algorithm improves the calculation time by 69.8% and the path quality by 6.1% compared with the traditional RRT* algorithm. It laid the foundation for the subsequent visual and tactile fusion of the robotic arm.