A Genetic Algorithm-Based Optimization Method for Manipulator Trajectory Planning

Abstract

The invention discloses a method for optimizing trajectory planning of a mechanical arm based on a genetic algorithm. It mainly includes the following steps: use the method of "parabolic interpolation - quintic spline interpolation - parabolic interpolation" to plan the trajectory of the manipulator in the joint space; on the basis of the current trajectory planning, use a genetic algorithm model with fitness function optimization The running time of the trajectory of the manipulator is handled favorably, so that the time of the manipulator is optimal during operation. The invention can generate optimized trajectory results of the mechanical arm, reduce the running time of the mechanical arm, improve the working efficiency of the mechanical arm, and ensure that the mechanical arm maintains stable and vibration-free operation during the rotation process. At the same time, the algorithmic solution process of the trajectory is relatively easy, and it can better realize the real-time control of the manipulator.

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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