Collision detection mechanical arm path planning method based on improved ant colony algorithm

Abstract

The invention relates to the field of mechanical arm kinematics control and planning, and discloses a collision detection mechanical arm path planning method based on an improved ant colony algorithm.The improved mechanical arm path planning method comprises the following steps of: performing kinematics analysis of a mechanical arm according to an established mechanical arm model, and completinga space mechanical arm kinematics inversion solution by correcting a Schmidt QR decomposition inversion method; considering the distribution condition of obstacles around selectable nodes, and improving the state transition probability of the ant colony algorithm; performing collision detection between the mechanical arm and the obstacle and between the mechanical arm and the mechanical arm connecting rod by adopting a cuboid envelope method; and searching an optimal path in the working space by the mechanical arm end executor, carrying out joint corner solving and collision detection, and finally realizing mechanical arm path planning. According to the method, a traditional mechanical arm path planning ant colony algorithm is improved for the mechanical arm path planning problem, the improved algorithm has a high convergence speed, the obtained path track is reasonable, and the obstacle avoidance effect is good.

Description

technical field [0001] The invention relates to the field of kinematics control and planning of a manipulator, in particular to a path planning method for a collision-detectable manipulator based on an improved ant colony algorithm. Background technique [0002] The path planning of the manipulator refers to finding an optimal path with the shortest distance from the initial point to the target point and avoiding obstacles to ensure its own safety on the basis of satisfying the working conditions. A path refers to a space curve formed by connecting discrete points, and does not contain the concept of time, and the strategy of searching for a path is called path planning. For a robotic arm, path planning is a set of specific sequences to find its own pose without considering the time factor of the pose. Usually, path planning mainly includes the work of environment modeling and search strategy. Among them, the environment modeling is to express the planning space in a mathe...

AI Technical Summary

Problems solved by technology

[0004] 1) Complexity

When the working environment of the manipulator is relatively complex, especially in a dynamic environment, the planning of the obstacle avoidance path is very complicated and the amount of calculation is huge;

[0005] 2) Difference

There are often multiple evaluation indicators for path planning, such as the shortest path, the least time, the lowest energy consumption, the highest safety factor, etc., and it is difficult to take into account different indicators at the same time

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