Research On Trajectory Planning Methods of Mobile Robots Based on SLAM Technology

Abstract

With the widespread adoption of mobile robots across various domains, the need for precise and efficient path planning has become paramount. Mobile robots, utilizing Simultaneous Localization and Mapping (SLAM) technology, achieve autonomous positioning and map construction, thereby laying a critical foundation for path planning. Consequently, this paper primarily focuses on path planning algorithms, encompassing SLAM, Dijkstra's algorithm, A* algorithm, and the Artificial Potential Field (APF) algorithm.The paper aims to provide a concise introduction to the fundamental principles of these algorithms, accompanied by a review of their practical applications across diverse fields. Additionally, it will discuss future developmental trends. Through an in-depth analysis of these algorithms, the paper seeks to elucidate their roles and advantages in mobile robot trajectory planning. Furthermore, it will objectively assess their limitations and disadvantages, thereby enabling readers to gain a comprehensive understanding of their real-world efficacy and potential constraints.Ultimately, the paper will undertake a comprehensive comparison and discussion of each algorithm, endeavoring to furnish readers with a thorough comprehension of mobile robot trajectory planning methods leveraging SLAM technology. It aspires to offer valuable insights and guidance for future research and practical endeavors in this domain.