Research On Path Planning And Obstacle Avoidance Method Of Mobile Robot

In recent years,robots have been widely used in the field of construction.However,there are many types and uneven distribution of obstacles in the construction environment,and sudden obstacles often occur randomly,making the environmental scenarios and types of obstacles encountered by many mobile robots in construction more complex.Based on the current practical situation of path planning for mobile robots and the research status of relevant scholars,the path planning algorithms used by most construction mobile robots currently have problems such as low path planning efficiency,poor dynamic obstacle avoidance timeliness,and low applicability in complex obstacle environments during construction.In order to improve the timeliness of path planning for mobile robots and the safety of practical applications,this article takes a four wheel differential mobile robot as the research object model,and proposes an optimized A * algorithm for effective expansion strategies and a global local path planning strategy that combines the optimized DWA algorithm with the attraction repulsion evaluation function for complex environments in construction scenarios.The main content of the paper is as follows:(1)Aiming at the traditional A* algorithm of global path planning in the path planning environment of complex obstacle distribution map,there are problems such as long path planning time and insufficient timeliness,an optimized A * algorithm based on effective expansion strategy is proposed to address these problems.Through comparative experiments on grid maps,the proposed optimized A * algorithm based on effective expansion strategy reduces the path length by about 8% and planning time by about 7% compared to the original algorithm.(2)Aiming at the problems of unreasonable trajectory evaluation selection and low obstacle avoidance efficiency when using the DWA algorithm in local path planning in construction obstacle scenes,an optimized DWA algorithm integrating the evaluation function of attraction and repulsion force is proposed.Through grid map comparison experiments,the proposed optimized DWA algorithm,which integrates the attraction repulsion evaluation function,optimizes the sampling times by 20% compared to the original algorithm,reduces the path length by 24%,and improves the running time by more than 10 seconds.(3)Combined with the A* and DWA algorithms before and after optimization,the comparison experiment,simulation experiment and actual experiment results show that,The proposed path planning and obstacle avoidance strategy of "Optimized A*algorithm based on effective expansion strategy + optimized DWA algorithm based on integration of attraction-repulsion evaluation function" can quickly plan a safe and effective global path in complex environment,and efficiently complete the obstacle avoidance task of unknown dynamic and static obstacles.