Optimal Path Planning of Automated Guided Vehicle using Dijkstra Algorithm under Dynamic Conditions

Sungkwan Kim, Hojun Jin, Minah Seo, Dongsoo Har
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引用次数: 23

Abstract

This paper presents an optimal path planning aiming at minimization of energy consumption and decrement of operation time of an automated guided vehicle (AGV) under dynamic operation conditions in a graph containing random slopes and distances. To convey one load to a desired- destination by AGVs is considered common practice in a logistic center. Loads of varying mass are transferred to desired-destinations in a graph composed of vertices and edges. In the graph, slopes and distances required for calculation of weight of edges are randomly given between a pair of vertices. Considering tractive forces of the AGV, a tractive force model is developed and this model is applied to path planning method. Mass variation of the AGV that occurs when it places the loads to each vertex is used for calculation of the energy consumption. According to the mass variation of an AGV and road conditions, the weights between vertices are determined. Based on the graph with the weights, the Dijkstra algorithm is applied to get an optimal path for the AGV. Proposed approach demonstrates minimization of AGV’s energy consumption and improvement of operation time with the optimal path.
动态条件下基于Dijkstra算法的自动引导车辆最优路径规划
在包含随机斜率和随机距离的图中,提出了一种动态运行条件下以能量消耗最小和运行时间最短为目标的自动导引车(AGV)最优路径规划方法。用agv将一件货物运送到指定的目的地是物流中心的常见做法。在由顶点和边组成的图中,不同质量的载荷被传递到期望的目的地。在图中,在一对顶点之间随机给出计算边权所需的斜率和距离。考虑AGV的牵引力,建立了AGV的牵引力模型,并将该模型应用于路径规划方法。当AGV将负载放置到每个顶点时发生的质量变化用于计算能量消耗。根据AGV的质量变化和道路状况,确定顶点间的权值。在权重图的基础上,应用Dijkstra算法求出AGV的最优路径。该方法利用最优路径实现了AGV能量消耗的最小化和运行时间的缩短。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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