Mechanical arm track planning and optimization method based on genetic algorithm

Abstract

The invention discloses a mechanical arm track planning and optimization method based on genetic algorithm. The method mainly comprises the following steps of making a plan for a mechanical arm trackbelow a joint space through the method of "parabolic interpolation, quintic spline interpolation and parabolic interpolation"; making optimization treatment to the running time of the mechanical arm track by adopting a genetic algorithm model for fitness function optimization on the basis of the current track planning, so that the time of the mechanical arm in the running process is optimal. According to the method, the optimized mechanical arm track result can be generated, and the running time of the mechanical arm is reduced; and the working efficiency of the mechanical arm is improved, andit is ensured that the mechanical arm is stably moved without shaking in the rotating process. Meanwhile, the solution process of the track algorithm is easier, and the real-time control of the mechanical arm can be achieved more easily.

Description

technical field [0001] The invention relates to a method for optimizing trajectory planning of a mechanical arm based on a genetic algorithm. Background technique [0002] With the continuous upgrading of the industrial revolution, the automation industry has become an indispensable part of modern industrial production. As the main force to promote the development of the automation industry, the robotic arm has received the most extensive attention and research. In the research process, not only the accuracy of the manipulator to grasp the target is required, but also the smooth and fast operation of the manipulator on the grasping track. Therefore, the result of the trajectory optimization of the manipulator directly affects the results of the operation and grasping of the manipulator. [0003] The existing trajectory planning for the robot arm in the joint space uses complex and high-order spline mixed interpolation methods to achieve the accuracy of the control of the e...

AI Technical Summary

Problems solved by technology

[0003] The existing trajectory planning for the robot arm in the joint space uses complex and high-order spline mixed interpolation methods to achieve the accuracy of the control of the end position of the robot arm, but all ignore the complexity of the pose solution algorithm process. The real-time performance of the manipulator is weakened; and the high-order spline and its mixed interpolation method are prone to jitter, repetition and other phenomena during the movement process; in the optimization method of trajectory planning, they are all optimized for specific goals, single-oriented and adaptable The dynamic performance of the degree function is weak, and the improvement of the trajectory optimization ability under different constraint environments is not obvious

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