Obstacle avoidance path planning for weaving robot based on improved artificial potential field method
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,correction coefficients are introduced and virtual obstacles are added when the weaving robot falls into the local minima,and 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.
NETL
NSTL
万方数据
维普
