超冗余柔性臂在狭小空间内改进RRT算法轨迹规划

Improved RRT Algorithm in Trajectory Planning for Super Redundant Flexible Arm in Narrow Space

为清理变电站联排变压器狭小空间内的异物,设计了一种超冗余多关节机械臂;根据机械臂的运动学特性在机器人工具箱建立了运动学模型,利用正运动学分析了万向节角度和驱动绳长,并利用蒙特卡洛法建立了机器人的工作空间;为缩短轨迹路线、减少随机树点数目,提出了基于改进后的RRT算法的轨迹规划方法,利用贪心算法进行轨迹优化,仿真结果显示路径长度减少20%且规划时间提高60%;利用多阶贝塞尔曲线进行轨迹平滑,降低轨迹路线曲率;改进后的RRT算法可以有效避障,且轨迹更为精确、曲率较小、处理速度更快,可以快速有效地完成异物清理工作。

To remove foreign objects in the narrow space of interconnection transformers in substations,a super redundant multi-joint robotic arm is designed.According to the kinematic characteristics of the robotic arm,the kinematic model is established in the robot toolbox,the positive kinematics is used to analyze the angel of gimbal and length of drive rope,a Monte Carlo approach is used to build the workspace of the robot.In order to shorten the trajectory route and decrease the number of random tree points,a trajectory planning approach based on the enhanced rapidly-exploring random tree(RRT)algorithm is proposed,and the trajectory optimization is carried out using the greedy algorithm,the simulation results show that the path length decreases by 20%and the plan time improves by 60%.A multi-order Bessel curve is adopted to smooth the trajectory and reduce the slope of the trajectory path.The improved RRT algorithm can effectively avoid obstacles,and the trajectory has the characteristics of more precise,smaller curvature,and faster processing speed.It can successfully and rapidly clean up foreign objects.