Intelligent route planning model of industrial robot based on inertia moment parameter optimization

Abstract

In order to improve the intelligent planning ability of monocular vision dynamic underactuated industrial robot's action route, an intelligent planning method of monocular vision dynamic underactuated industrial robot's action route based on inertia moment parameter optimization is proposed. Establishing a spatial grid area planning model of monocular vision dynamic underactuated industrial robot action route, adopting a cell moment parameter optimization method to carry out grid regionalization matching in the process of monocular vision dynamic underactuated industrial robot action route optimization planning, establishing optimization constraint parameters of monocular vision dynamic underactuated industrial robot action route distribution. Based on kinematic feature analysis method, the optimization planning and moment parameter optimization analysis of monocular vision dynamic underactuated industrial robot are carried out. Through automatic condition tracking feedback and moment parameter optimization analysis, the path optimization of monocular vision dynamic underactuated industrial robot is realized. Combined with unsupervised learning algorithm of fuzzy PID network, the intelligent planning model of action route is constructed to improve control stability. Tests show that this method has good adaptability and strong obstacle avoidance ability for monocular vision dynamic underactuated industrial robot.