Path Planning of Apple Picking Robot Arm Based on Informed RRT
Aiming at the problems of low success rate and long planning time of harvesting robots in unstructured and complex environments,an improved harvesting motion planning algorithm based on informed RRT*is proposed.In the improved algorithm,P probability sampling is used instead of random sampling to improve the targeting of sam-pling and generate sub nodes with dynamic step size.The improved algorithm has increased the speed and flexibility of the Informed RRT*algorithm in exploring unknown spaces,and improved the convergence speed of the optimal path.Two dimensional simulation experiments show that compared with Informed RRT*,the improved algorithm can shorten the initial path query and have a higher success rate.Through 3D simulation experiments,it can be seen that the improved harvesting robotic arm planning algorithm proposed in this paper achieves fast path queries,improves planning query rates,reduces blind indexing,and verifies the effectiveness and superiority of the algorithm.
harvesting robotmotion planningrobotic arm improvementinformed-RRT* algorithm
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