A dynamic obstacle avoidance path planning method for a seven-degree-of-freedom redundant manipulator based on fast random search tree

Abstract

The invention discloses a dynamic obstacle avoidance path planning method of a seven-degree-of-freedom redundant manipulator based on a fast random search tree, including offline planning and online planning, and the offline planning uses the analytical solution of the inverse kinematics of the redundant manipulator to determine the optimal target State, as the target node to build a search tree, online planning on the obtained search tree to expand and rewire the tree according to the current environment, to obtain a path from the target node to the root node in real time, and when the manipulator moves, the tree The root node of the node also changes accordingly. If the target node is blocked by obstacles, the target node is switched, and a new path is searched to avoid dynamic obstacles. Through offline and online two-step planning, the present invention solves the problem that the redundant manipulator cannot be used for real-time obstacle avoidance due to the high computational complexity of RRT*, and solves the dynamic problem by updating the root node and target node of the search tree in real time. The problem of unreachable target nodes in the environment ensures real-time planning of a collision-free path for the manipulator.

Description

technical field [0001] The present invention relates to the field of path planning of multi-degree-of-freedom manipulators, in particular to a dynamic obstacle-avoiding path planning method for seven-degree-of-freedom redundant manipulators based on fast random search trees. Background technique [0002] Robot path planning is a basic problem in the field of robotics research, which aims to find a path for the robot from the initial state to the goal state, and safely avoid all obstacles in the motion space. Scholars at home and abroad have proposed many effective path planning methods for mobile robots, such as A* algorithm, Dijkstra algorithm, etc. At this time, the mobile robot is often simplified into a mass point with kinematic constraints. However, the manipulator is a multi-input and multi-output, highly nonlinear, and strongly coupled complex system, which cannot be directly regarded as a particle in Cartesian space, so most path planning methods for mobile robots ca...

AI Technical Summary

Problems solved by technology

However, the manipulator is a multi-input and multi-output, highly nonlinear, and strongly coupled complex system, which cannot be directly regarded as a particle in Cartesian space, so most path planning methods for mobile robots cannot be directly extended to manipulators.

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