改进RRT-人工势场法的机械臂堆垛运动方法

快速拓展随机树算法(RRT)在机械臂路径规划中存在随机性强、搜索效率低、规划路径长等问题,不能在货柜堆垛场景中取得相对最优的光滑路径.对此,该文提出了一种改进RRT-人工势场法混合算法进行货柜堆垛机械臂运动规划.首先,对传统快速拓展随机树算法进行改进,在传统快速拓展随机树算法的全局搜索的基础上引入目标搜索,增强了随机树...

Improved RRT-Artificial Potential Field Method for Robotic Arm Stacking Movement Method

The rapidly exploring random tree(RRT) has some problems in the path planning of the robot arm, such as strong randomness, low search efficiency and long planning path, which cannot obtain the relatively optimal smooth path in the container stacking scene. For this, we propose an improved RRT-artificial potential field method, a hybrid algorithm, for the motion planning of the container stacking manipulator. Firstly, the traditional RRT is improved. The target search is introduced on the basis of the global search of the traditional RRT to enhance the search efficiency of the random tree, and the improved algorithm is used for global path planning. Secondly, the artificial potential field method is improved. The gravity function is modified by using the range of repulsive potential field as the threshold, the repulsive force function is modified by using the influence of the manipulator end-effector to the last position point, and the local path is optimized by using the improved artificial potential field method. Thirdly, a cubic non-uniform B-spline curve is used to smooth the path, which is used as the final path of the end effector of the robot arm. Finally, the reliability analysis of the improved algorithm is carried out in Python simulation scene, and the application simulation of the robotic arm stacking movement in the ROS system verifies the effectiveness and feasibility of the proposed method.