An Efficient RRT Algorithm for Motion Planning of Live-Line Maintenance Robots

Abstract

The application of robots to replace manual work in live-line working scenes can effectively guarantee the safety of personnel. To improve the operation efficiency and reduce the difficulties in operating a live-line working robot, this paper proposes a multi-DOF robot motion planning method based on RRT and extended algorithms. The planning results of traditional RRT and extended algorithms are random, and obtaining sub-optimal results requires a lot of calculations. In this study, a sparse offline tree filling the planning space are generated offline through the growing–withering method. In the process of expanding the tree, by removing small branches, the tree can fully wiring in the planning space with a small number of nodes. Optimize wiring through a large number of offline calculations, which can improve the progressive optimality of the algorithm. Through dynamic sampling and pruning, the growth of trees in undesired areas is reduced and undesired planning results are avoided. Based on the offline tree, this article introduces the method of online motion planning. Experiments show that this method can quickly complete the robot motion planning and obtain efficient and low-uncertainty paths.