基于拉格朗日分解技术的多移动机器人分布式路径规划方法

T. Nishi, Masakazu Ando, M. Konishi, J. Imai
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引用次数: 23

摘要

对于半导体制造车间的运输,多台agv(自动导引车)的路线规划是最小化总运输时间,避免agv之间的碰撞和死锁。本文提出了一种基于拉格朗日分解技术的多移动机器人分布式路径规划方法。该方法的特点是通过agv之间的重复数据交换和Dijkstra算法的局部优化,每个移动机器人单独创建一个接近最优的路径。该方法已成功应用于半导体加工车间的运输路线规划问题。利用拉格朗日松弛法导出的对偶间隙,对该方法生成的解的最优性进行了评价。对于由143个节点和15辆agv组成的大型运输系统,只需在5秒的计算时间内,就可以在5%的对偶间隙内获得近似最优解。以3台AGV系统为例,给出了考虑AGV大小的路径规划。实验结果表明,该方法对各种类型的问题都是有效的,尽管AGV的每条路径都是在不考虑整个目标函数的情况下创建的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A distributed route planning method for multiple mobile robots using Lagrangian decomposition technique
For the transportation in semiconductor fabricating bay, route planning of multiple AGVs (Automated Guided Vehicles) is expected to minimize the total transportation time without collision and deadlock among AGVs. In this paper, we propose a distributed route planning method for multiple mobile robots using Lagrangian decomposition technique. The proposed method has a characteristic that each mobile robot individually creates a near optimal route through the repetitive data exchange among the AGVs and the local optimization of its route using Dijkstra's algorithm. The proposed method is successively applied to transportation route planning problem in semiconductor fabricating bay. The optimality of the solution generated by the proposed method is evaluated by using the duality gap derived by using Lagrangian relaxation method. A near optimal solution within 5% of duality gap for a large scale transportation system consisting of 143 nodes and 15 AGVs can be obtained only within five seconds of computation time. The proposed method is implemented on 3 AGVs system and the route plan is derived taking the size of AGV into account. It is experimentally shown that the proposed method can be found to be effective for various types of problems despite the fact that each route for AGV is created without considering the entire objective function.
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