Using neural networks to explore path planning algorithms for robots

Abstract

In the introduction section of this paper, the importance of path planning for automatic self-navigation is outlined, along with the structure and basic model of neural networks, as well as numerous practical examples of using neural networks to solve the problem of traffic prediction and autonomous robot navigation. In the method section, the specific formulations and steps of how neural networks can be used to solve the path planning problem are explained in detail. Additionally, a variety of algorithms for solving the path planning problem with neural networks are introduced, and practical experiments are conducted to compare the results of these algorithms in various environments. In the RESULTS section, the characteristics are summarized and explained by comparing the experimental results. In the CONFUSION section, a fundamental outlook on the future of neural networks for solving path-planning problems is provided, as well as the possibility of cooperation between neural networks and other methods for solving path-planning problems.