Research On Path Planning Algorithms Of Intelligent Unmanned Vehicle For Storage

With the continuous expansion of the storage scale of modern enterprises,more and more enterprises have introduced intelligent unmanned vehicles for handling and sorting in the storage system.And a good intelligent vehicle path planning algorithm for intelligent unmanned vehicles can effectively improve the efficiency and security of the storage system.The path planning algorithm of intelligent unmanned vehicle for storage is studied in this paper.Based on the overview of the development of the technology and the common path planning algorithm of the intelligent self driving vehicle,the principles of several commonly used path planning algorithms are analyzed,and the two parts of the intelligent vehicle's global path planning and local path planning are studied.Considering the environment of the storage system and the efficiency of the unmanned vehicle,we focus on the path planning algorithm based on the short distance and the small amount of calculation.Aiming at the global path planning part,based on the classical A*algorithm,an improved A*algorithm based on the topology environment model is proposed.It can effectively reduce the amount of computation in search process when searching the global optimal path successfully.Aiming at the partial path planning part,based on the classical artificial potential field method,an improved artificial potential field method is proposed,and the target unreachable problem is solved by improving the repulsive potential field function.On this basis,the local minimum problem is solved by setting the method of subtarget point.Then,we integrate the global path planning algorithm and the local path planning algorithm,and propose a hybrid algorithm of path planning for warehousing autonomous vehicle,which is adapted to different warehouse environments through decision modules.Simulation results prove the feasibility of the method.Finally,the motion control algorithm and software of two wheel differential driving self driving vehicle are designed,and the hardware experimental platform of the driverless vehicle is built.The effectiveness and practicability of the proposed algorithm is verified by experiments.