Study on Remote Operation Obstacle Avoidance of Robotic Arm by Fusing APF and RRT Algorithms

摘要

In order to solve the problems of high delay and difficult obstacle avoidance at the controlled end during remote operation, a path planning algorithm based on artificial potential field (APF) and rapidly exploring random tree (RRT) is proposed. Firstly, through the effective suppression of obstacle repulsion and the equipotential movement method, the traditional APF algorithm solves the problem of path point oscillation and falling into local minima; secondly, the improved RRT algorithm based on the goal-oriented algorithm is proposed, which solves the problem of the traditional RRT algorithm's large randomness and slow path planning efficiency; lastly, in order to solve the problem that APF algorithm's path planning is single, which can not satisfy the obstacle avoidance of the robotic arm body, the APF algorithm based on the integration of RRT algorithm on the collision point secondary planning, to achieve the high efficiency of the robotic arm path planning and obstacle avoidance. Experiments prove that the improved APF algorithm avoids the problem of path oscillation and can jump out of the local minima. Comparing the APF fusion RRT algorithm with the traditional RRT algorithm in the environment with and without obstacles, the planning time is reduced by 32.12% and 33.43%, and the obstacle avoidance function is realized.