基于改进人工势场法的机织机器人避障路径规划

Obstacle avoidance path planning for weaving robot based on improved artificial potential field method

针对机织机器人自动化作业时的避障问题,提出基于改进人工势场法的三维避障路径规划算法。利用改进人工势场法中斥力势场函数,引入修正系数,在机织机器人陷入局部极小值点时增加虚拟障碍物,破坏其在虚拟力下的平衡状态,解决了人工势场法无法到达目标位置和局部极小值点的问题。通过体素化网格方法和快速凸包算法处理障碍物点云数据,重建实际障碍物模型,提高了碰撞检测效率。仿真结果表明,以点云数据重建障碍物模型并采用改进人工势场算法规划出的避障路径使机织机器人成功到达目标位置,末端位置精度平均提高37%,并避免陷入局部极小值点。

The 3D obstacle avoidance path planning algorithm based on the improved artificial potential field method is proposed for the obstacle avoidance problem in the automated operation of weaving robots.Using the repulsive potential field function in the artificial potential field method,introduce correction coefficients are introduced and add virtual obstacles are added when the weaving robot falls into the local minima,and destroy its equilibrium state under the virtual force is destroyed,so as to solve the problem that the artificial potential field method cannot reach the target location and local minima.Obstacle point cloud data was processed by voxelized grid method and fast convex packet algorithm to reconstruct the actual obstacle model,which improves the efficiency of collision detection.The simulation results show that the obstacle avoidance path planned by reconstructing the obstacle model with the point cloud data and using the improved artificial potential field algorithm enables the weaving robot to reach the target position successfully,and the end position accuracy is improved by 37%on average,and avoids falling into the local minima point.