Research On Autonomous Obstacle Avoidance And Path Planning Algorithm For AGV In Complex Environment

In recent years,mobile robots are playing a vital role in industry and commerce,and Automatic Guided vehicles(AGV)is playing a vital role in warehousing,logistics,hospitals and factories,and are widely used as important tools in all walks of life.Because they can operate in hazardous environments with minimal manual input.How to design efficient adaptive obstacle avoidance and path planning algorithm is the key problem in AGV research.Therefore,it is of great significance to study the autonomous obstacle avoidance and path planning algorithm of AGV for promoting the development of robot technology,realizing intelligent manufacturing and improving logistics efficiency.In this paper,the application scenarios of AGV and the global path planning and local obstacle avoidance algorithm of AGV is studied in depth,and an intelligent obstacle avoidance path planning algorithm combining the improved A~*algorithm and the improved DWA(dynamic window approach)algorithm is proposed,which improves the safety and obstacle avoidance effect of AGV in complex environment.The main research contents are as follows:1.To solve the problem of autonomous obstacle avoidance algorithm of AGV,this paper proposes an improved DWA algorithm as the local obstacle avoidance algorithm of AGV.The tangent vector of the differential manifold is introduced to improve the trajectory space and smooth path of the selection.Then the evaluation function is improved by introducing the subfunction of the number of obstacles and the new subfunction of the change of direction Angle to optimize the DWA algorithm.Finally,MATLAB and ROS simulation experiments are used to verify the effectiveness and feasibility of the improved DWA algorithm.2.In view of the high spatial complexity and too many inflection points in the path planning problem of traditional A~*algorithm,expanding the number of nodes and weight factor are proposed to improve the security and search performance of the algorithm,and Bezier curves are introduced to smooth the trajectory optimization.Then MATLAB simulation experiments are used to verify the feasibility and effectiveness of the improved A~*algorithm.3.An experimental platform based on AGV and ROS(Robot Operating System)was built to verify the path planning and obstacle avoidance experiments of AGV combined with improved A~*algorithm and improved DWA algorithm.The experimental results show that the fusion of the improved A~*algorithm and the improved DWA algorithm is better in global path planning and real-time obstacle avoidance effect.