基于CTB-RRT*的果蔬采摘机械臂运动路径规划

Motion Planning of Picking Manipulator Based on CTB-RRT*Algorithm

针对多自由度果蔬采摘机械臂运动路径规划速度慢、效率低、路径成本高的问题,提出了柯西目标引力双向RRT*(Cauchy target gravitational bidirectional RRT*,CTB-RRT*)算法,通过柯西分布的方法进行启发式采样,降低采样的盲目性;引入目标引力,并动态调节随机生长方向和目标方向的步长,提高局部搜索速度;引入节点拒绝策略,剔除不必要的采样节点,提高计算效率。通过二维和三维算法模拟实验,6自由度机械臂的避障采摘模拟实验验证了提出算法的有效性。仿真实验结果表明:相比于RRT*-connect算法,改进算法的路径成本缩短了5.5%,运行时间降低了71.8%,采样节点数下降了64.2%。在机器人操作系统(Robot operating system,ROS)中控制6自由度机械臂执行避障采摘运动,运动成功率达到99%,运行时间为0.33 s,相比于RRT*-connect算法,路径成本降低了12.6%,运行时间减少了69.2%,扩展节点数减少了76.3%。

Aiming at the problems of slow motion planning,low efficiency,and high path cost of multi-degree-of-freedom picking manipulators.The Cauchy target gravitational bidirectional RRT*(CTB-RRT*)algorithm was proposed.Heuristic sampling was carried out by Cauchy distribution method to reduce the blindness of sampling.Through introducing target gravity,the step length of the random growth direction and the target direction were dynamically adjusted to improve the local search speed.What’s more,a node rejection strategy was introduced to eliminate unnecessary sampling nodes and improve calculation efficiency.Through two-dimensional and three-dimensional algorithm simulation experiments,the 6-DOF manipulator's obstacle avoidance picking simulation experiment verified the effectiveness of the proposed algorithm.The results of research and simulation experiments showed that the path cost of the improved algorithm was reduced by 5.5%,the search time was reduced by 71.8%,and the number of sampling nodes was reduced by 64.2%,comparing with the RRT*-connect algorithm.To verify the feasibility of the algorithm,the 6-DOF manipulator was controlled to perform obstacle avoidance picking movement in the robot operating system(ROS).The success rate of motion was 99%,and the running time was 0.33 s.Comparing with the RRT*-connect algorithm,the path cost was reduced by 12.6%,and the running time was reduced by 69.2%.The number of expansion nodes was reduced by 76.3%.