Application of Robot Autonomous Navigation Based on Reinforcement Learning

Abstract

Currently, with the rapid development of robotics technology, autonomous navigation of robots has become an important research field. Traditional navigation methods have certain limitations in complex environments and dynamic tasks, while reinforcement learning, as a powerful machine learning paradigm, provides an effective solution for autonomous navigation of robots. This article first introduces the basic concepts of robot autonomous navigation and the challenges faced by traditional navigation methods, and then introduces the basic principles of reinforcement learning. Then, the modeling of robot autonomous navigation based on reinforcement learning was introduced, and the different application methods of reinforcement learning algorithms in robot autonomous navigation and the response of reinforcement learning to navigation tasks in complex environments were elaborated. Finally, the autonomous navigation performance of robots based on reinforcement learning algorithms was demonstrated through multiple experimental cases.