Global path planning algorithm of industrial robot based on neural network

Path planning is also an indispensable and important part in the development of intelligent robot technology. Path planning generally refers to that the robot finds a safe and unimpeded path of collision with obstacles from the initial working state to the end target state according to a certain standard of safety evaluation in advance in any working environment with the characteristics of collision obstacles. The principle of artificial potential field method is to find the energy on the path point through artificial method, so as to obtain the problem of energy combination explosion by making the path point avoid obstacles or overcome obstacles. Therefore, based on neural network algorithm, this paper also makes a preliminary and in-depth study on some global path planning and optimization problems required by the development of industrial robot system in the future. Firstly, this paper describes the relevant background, significance and technology. This paper expounds the use of such a method that can decompose a global path planning process into multiple local sub path planning problems to help solve the application of industrial robot technology in solving many practical traffic problems. Finally, the test results show that the system meets the actual needs.