A motion path planning method and system for a humanoid robotic arm

Abstract

The invention discloses a humanoid mechanical arm movement route planning method and system. The method includes the steps that the start position and the target position of the to-be-moved space of ahumanoid mechanical arm are determined according to a D-H model of the humanoid mechanical arm; a sampling point of the to-be-moved space of the humanoid mechanical arm is explored through a rapidlyexploring random tree method, and in the exploring process, a random sampling point is determined through a bias probability sampling algorithm; and new node extension is conducted according to the determined random sampling point, and through combination with a new node, an extension random tree with the start position as a source and the target position as a terminal node is established. Finally, the route with the minimum total weight is found in all routes of the established extension tree, information of all nodes in the route with the minimum total weight is solved into joint angle information of humanoid mechanical arm movement through inverse kinematics, and the humanoid mechanical arm is made to move according to the joint angle information. By means of the humanoid mechanical armmovement route planning method and system, the search time can be saved, and the sampling point searching speed can be increased.

Description

technical field [0001] The invention relates to the technical field of motion planning of a mechanical arm, in particular to a method and system for planning a motion path of a humanoid mechanical arm. Background technique [0002] In recent years, with the continuous development of production technology, the application of manipulators has become more extensive, and the requirements for the operation accuracy of manipulators have also been continuously improved. For the robotic arm to complete a complete operation process, it is required that the robotic arm can reach the predetermined position quickly and accurately before performing the operation. There are many paths that a robotic arm can travel, but finding a path that satisfies both motion constraints and metrics has always been the goal of motion planning for a robotic arm. The optimal path generally includes conditions such as the shortest path, the shortest use time, and the least energy loss. [0003] Existing m...

AI Technical Summary

Problems solved by technology

It is worth noting that this algorithm does not provide an optimal solution because the exploration tree of the search path is expanded by randomly sampled points

In addition, the RRT algorithm adopts a global uniform random sampling strategy, which has a slow convergence speed and consumes a lot of time

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