Research On Scheduling And Path Optimization Of Multiple Mobile Robots

Multi-robot collaboration is the basic technology of intelligent manufacturing,many scholars at home and abroad have studied the problem of job scheduling and path planning in multi-robot collaboration.In this article,a method of job scheduling and path optimization for multi-mobile robots using Hopfield neural network,improved ant colony algorithm and time window is proposed.The thesis firstly describes the system structure of the multi-mobile robot from three aspects: operation environment,map model and operation flow,introduces control method of multi-robot.And the scheduling algorithm model and performance evaluation method of multi-mobile robot system are presented.In order to improve the efficiency of multi-robot task assignment,a Hopfield neural network algorithm is proposed to solve the multi-robot task assignment problem.According to the characteristics of multi-robot operation,the energy function expression corresponding to the constraint condition is designed,and the Hopfield neural network structure and weight expression for the multi-robot scheduling problem in the workshop are acquired,then a feasible and efficient multi-robot task scheduling scheme is obtained.In view of the fact that the path planning algorithm is inefficient and prone to local optimality,an improved ant colony algorithm based on three optimization strategies is proposed.Firstly,the difference between the previous generation optimal path and the current optimal path in ant colony algorithm has dynamic change information,and the algorithm efficiency can be improved through feedforward generated by dynamic change information.The second is to improve the heuristic factor of the algorithm and make full use of the heuristic information of the destination to improve the low efficiency of the algorithm in the early stage of search.Third,adding mutation operation to the improved ant colony algorithm to solve the problem that the ant colony algorithm is prone to local optimality,so as to improve the efficiency of the robot path planning algorithm.To solve the problem of path collision of mobile robots,a multi-robot cooperative obstacle avoidance strategy based on time window algorithm is proposed.This thesis presents a method for calculating the conflict zone and a time window assignment method for crossing two or more paths.Finally,the thesis fuses the results of global task assignment and path optimization to form a complete intelligent scheduling algorithm for factory multi-robot.The effectiveness and practicability of the proposed algorithm in optimizing the scheduling and path planning of multi-mobile robots are verified by simulation experiments and comparison with similar methods.