Research On Motion Planning Methods Of Mobile Robots

Mobile robots,as an important branch of the robotics field,have developed rapidly in recent years.They are widely used in industrial production,survey and search,service industry,logistics industry and agricultural production,and other fields.Motion planning method is one of key technologies of mobile robots and is crucial for ensuring stability and safety of robot motion.This paper studies path planning algorithms and trajectory planning algorithms for motion planning methods of mobile robots,and verifies the algorithms on a simulation environment and a physical prototype platform.The main research content of this paper are as follows:1.In response to the problems of low search efficiency,poor real-time performance,and a large number of redundant road sections in the traditional A* algorithm,the neighborhood search range of A* algorithm is optimized,and a path key point extraction method is proposed.The improved algorithm is simulated and validated on a multi-scale grid map.The experimental results show that,compared with traditional algorithms,the algorithm has improved in indicators such as path length,search time,number of path nodes,and number of inflection points,verifying the effectiveness of the improved algorithm.2.In response to the problems of frequent turns and unsmooth trajectories in the traditional dynamic window approach,its evaluation function is optimized and the improved A* algorithm is integrated with it.In order to enable the robot to smoothly cross obstacles while quickly heading towards the target node,a distance evaluation function for the target point is added,and the coefficients of the distance evaluation function for obstacles are dynamically adjusted.The simulation results show that the improved dynamic window approach has certain improvements in motion duration,average speed,and iteration times,verifying the effectiveness of the improved algorithm.3.In order to validate the proposed algorithm,a physical prototype of a wheeled mobile robot and a software system based on ROS are built.Migrate the improved fusion algorithm to the robot navigation system and conduct path planning,trajectory planning,dynamic obstacle avoidance,and autonomous navigation experiments in both simulated and real environments.Experimental results show that the improved fusion algorithm can plan better paths in both static and dynamic environments,with higher planning efficiency and smoother motion trajectories,verifying the superiority of the improved algorithm and effectively improving various motion performance of mobile robots.