Industrial robot trajectory optimization method based on improved genetic algorithm

A technology for improving genetic algorithms and industrial robots, applied in the field of trajectory optimization of industrial robots based on improved genetic algorithms
CN112692826AActive Publication Date: 2021-04-23FOSHAN UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
FOSHAN UNIVERSITY
Publication Date
2021-04-23

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Abstract

The invention discloses an industrial robot trajectory optimization method based on an improved genetic algorithm, and aims to provide a trajectory through which an industrial robot completes a given route with the shortest time and the minimum impact based on the given path and a certain constraint condition. Based on a traditional genetic algorithm, the industrial robot trajectory optimization method disclosed by the invention improves a gene selection formula, a crossover formula and a mutation formula, improves crossover and mutation probabilities on the basis of self-adaption PRGA, optimizes the action time of a mechanical arm under the condition that the motion trail of the robot is stable, reduces resonance and shaking, caused by overlarge impact, of the robot, and enables the robot to run stably and smoothly, thereby greatly improving the working efficiency and prolonging the service life of the robot.
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Description

Technical field

[0001] The present invention belongs to the technical field of robot trajectory planning, and specific relates to an industrial robot trajectory optimization method based on improved genetic algorithm.Background technique

[0002] The industrial robot has the advantages of high-speed high-precision, safe and reliable, etc., in modern industrial automation applications such as welding, spray coating, more actual significance. The existing robot trajectory planning is generally the joint angle, speed, and acceleration parameters of manual arms after a given trajectory, through the instrument, and the workforce is liberated to a certain extent, this method is It is based on artificial experience to set parameters, and cannot reach the shortest run time. The final running trajectory is not necessarily smooth, and there may be impact, which causes the mutation to shorten the life of the robot. Therefore, the appropriate method must be selected in the actual production applicati...

Claims

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