Research On Path Planning Of Mobile Robots For Warehousing Logistics

With the rapid development of e-commerce,the logistics industry under intelligent warehouse is also booming.The use of mobile robots has gradually become the prerequisite for robots to complete complex tasks,the success of the plan determines whether the mobile robot can accomplish tasks efficiently,safely and autonomously.At present,the path planning of mobile robots with only static obstacles in warehouse environment is quite mature,but for the case of dynamic obstacles with unknown motion state in the environment,the research of local path planning technology of mobile robots has become a difficult problem,which needs further exploration and research.In this paper,a real-time and feasible path planning method for warehousing logistics environment with both static and dynamic obstacles is studied.The purpose is to improve the ability of mobile robots to perceive warehousing environment in time and to make corresponding judgments.The focus of traditional ant colony algorithm is deeply studied,and the solution is given.In this paper,based on warehousing logistics environment,the path planning problem of mobile robots in global static obstacle environment is analyzed and solved,and the path planning problem of mobile robots with known global static environment but some unknown dynamic obstacles in advance is solved.The main work includes:1.The improvement of the pheromone update method in the ant colony transition probability can solve the problem that the traditional ACA converges too slowly in the initial stage of operation.By increasing the pheromone concentration in ACA transition probability function and adjusting the value of state transition probability by adaptive method,the search speed can be improved and the diversity of solutions can be enhanced.In this paper,through simulation experiments,the advantages of the improved ACA proposed in this paper for mobile robot path planning in the environment of only static obstacles in warehouse logistics are discussed.2.On the basis of the improved ant colony algorithm with elite strategy,a smoothing method based on the center point is added.This method makes the smaller turning angle in the path smoother,reduces the energy loss of the robot at the turning point of the path,ensures the stability of the robot entity in the process of moving,and solves the practical problems that the mobile robot in warehouse logistics will encounter in the process of moving forward.The simulation results show the practicability of the proposed algorithm.3.Aiming at the problem of path planning for mobile robots with dynamic obstacles in warehousing environment,this paper adopts the method of combining global static path planning with local dynamic collision avoidance planning.Firstly,in warehousing environment without considering dynamic obstacles,an improved ACA is used to plan a global optimal collision-free path;secondly,the foundation of global path planning is completed.On the basis of rolling window detection,this paper introduces a rolling window-based method to detect the running environment of the robot.For the planned walking path of the robot,it can detect whether it will collide with the dynamic obstacles in the running environment of the warehouse robot in advance.On the basis of rolling window detection,the obstacle avoidance corresponding to the mobile robot in various situations with different running status of the obstacles is proposed.The strategy is to use the improved ACA to plan the optimal path for the robot to walk and avoid dynamic obstacles.The simulation results show that the proposed method can effectively avoid dynamic obstacles in open-loop environments.