Obstacle Avoidance Motion Planning of Manipulators in ROS Based on the Improved RRT Algorithm - Cao Yi; Zhang Jingtao; Zhao Pu; Li Lei; Guo Yinhui (Jixie chuandong)
Aiming at the fact that the RRT algorithm based on the target bias is easy to fall into local search and has a low search efficiency in complex environment, further improvement is made in the ROS based on the Dobot model and the DIY model. On the basis of creating the manipulator model, the MoveIt! is used for configuration and the model is simplified to improve the efficiency of the collision detection. The extended target change strategy and variable step size are introduced to improve the algorithm which is based on the target biased RRT algorithm. The simulation of the manipulator obstacle avoidance motion planning under different forms of obstacles is carried out in the ROS. The experiments of the obstacle avoidance and obstacle avoidance grasping are carried out on the prototype. Simulation and experimental results show that the proposed improved RRT algorithm can improve the planning success rate and efficiency by 42.9% and 29.2% respectively compared with the RRT algorithm based on target bias.