Research on Robot Path Planning and Localization Based on ROS

Recently, the rapid development of robotics technology has made enhancing autonomous navigation capabilities in complex environments increasingly essential. Path planning is key to improving the autonomy of robots, while localization is the process of determining the robot’s accurate position within the environment. Given this, this research delves into path planning and localization technologies based on the Robot Operating System (ROS), comparing and analyzing path planning algorithms such as Dijkstra, A*, RRT and its variants, as well as particle filter localization techniques. By discussing the performance of these technologies in practical applications, we highlight their strengths and weaknesses in high-dimensional spaces and complex terrains and proposes corresponding optimization strategies to enhance robots’ navigation capabilities in complex environments. The research indicates that the appropriate combination of various path planning and localization technologies in different application scenarios can effectively improve the performance of robotic systems, providing a theoretical basis and practical guidance for the optimization of robotic navigation systems.