Path Planning And Application Of Indoor Warehouse Logistics Robot

In recent years,with the continuous progress of science and technology,warehousing and logistics robots are used in different fields.In the complex storage environment,the storage robot has poor obstacle avoidance ability and the planned path does not meet the global optimal.Therefore,this paper focuses on the path planning of the storage and logistics robot.Aiming at the problem of too many turning points and too long path planned by traditional A~* algorithm,this paper uses A~*algorithm for global path planning and proposes an improved A~* algorithm.DWA algorithm is used for local path planning.Due to the disadvantages of using a single algorithm for path planning,the two algorithms are considered to be integrated.Therefore,a fusion algorithm based on the improved DWA algorithm is proposed in this paper,and the path planning of fusion algorithm is studied from the aspects of theory,simulation and practical verification.The main research methods are as follows:(1)Global path planning based on improved A~* algorithm.In order to solve the problem that the traditional A~* algorithm has fewer search nodes,more path turning points,and the planned path does not meet the global optimality,this paper extends the search neighborhood of A~* algorithm from the original 8 neighborhood to 20 neighborhood.Since the expansion of nodes will reduce the search efficiency of the algorithm,dynamic weighting is carried out on the heurizing function of A~* algorithm.In order to reduce the turning point of the path,the method of bidirectional node removal is adopted.Experimental results show that the improved A~* algorithm has better performance.(2)Fusion algorithm based on improved DWA algorithm.Due to the poor obstacle avoidance performance of the traditional DWA algorithm,the fit degree of the planned local path and the global path is not high,so this paper improved the evaluation function of the DWA algorithm,adding the unknown obstacle gap evaluation subfunction and the backward node direction evaluation subfunction to the original evaluation function.Moreover,the improved A~* algorithm is fused with the traditional DWA algorithm and the improved DWA algorithm respectively.The simulation experiment proves that the improved fusion algorithm reduces the path length and time of the car,and increases the speed of the car.(3)Simulation experiment based on ROS platform.In order to verify that the improved fusion algorithm proposed in this paper can be applied in the actual environment,a warehouse environment was built in the laboratory,and simulation verification was carried out on Rviz.The experimental results confirmed the feasibility of the fusion algorithm.