Obstacle Avoidance Path Planning Research for Robotic Arm of the Power-carrying Operation Robot based on Improved RRT Algorithm

Abstract

The robotic arm of the power-carrying operation robot faces path planning challenges in complex distribution network environments. Addressing these challenges is crucial for optimizing the robot's performance and efficiency., this paper proposes an improved Rapidly-exploring Random Tree (RRT) obstacle avoidance algorithm. The algorithm improves the efficiency and accuracy of path planning by introducing a dynamic sampling function. This function allows for the dynamic adjustment of sampling points based on the distribution of obstacles. Combined with the cost function of the A* algorithm, the path is further simplified and smoothed to reduce the inflection points and optimize the motion trajectory of the robot's robotic arm. The simulation results verify the efficiency of the algorithm in reducing the path planning time and path length, in which the number of sampling points is reduced by 70.3% and the planning time is shortened by 68.3% in the 3-dimensional(3D) simulation, which proves its effectiveness in the field of power-carrying operation robot.