Intelligent Robot Path Planning and Navigation based on Reinforcement Learning and Adaptive Control

. Intelligent robot path planning and navigation has important applications and significance in the field of modern automation and artificial intelligence. The aim of this study is to explore how reinforcement learning and adaptive control can be used to improve the path planning and navigation performance of intelligent robots. Through a comprehensive analysis of relevant literature, this article reviews the application of reinforcement learning in robot path planning and navigation and the research progress of adaptive control theory and methods. Based on the construction of the theoretical framework and methods, this article proposes a new path planning and navigation method and conduct experimental validation. The experimental results show that the method based on reinforcement learning and adaptive control achieves significant improvements in path planning and navigation of intelligent robots. Finally, this article summarises the main findings of the study and provide an outlook on future research directions. The significance of this study is to promote the development of the field of path planning and navigation for intelligent robots, and to provide important theoretical and methodological support for realising intelligent robots to complete tasks efficiently and accurately in complex environments.