agv自動導(dǎo)航車中英文資料外文翻譯文獻(xiàn)(編輯修改稿)
2025-01-11 13:05 本頁面
【文章內(nèi)容簡介】 ing idle vehicles and, managing batterycharging scheme. Finally, vehicle routing, deadlock resolution (and prevention) problems are addressed at operational level. During the design and control processes, some interactions and iterations can be seen between steps. For example, the type of the guidepath system directly influences the number of vehicles required and the plexity of the vehicle scheduling system. Fig. 1 The guidedvehicle system of a distribution center Traditional AGV systems use fixed guidepaths for vehicles. Modern AGV systems differ from the classic ones as described, for instance, in the books of J252。nemann and Schmidt (2021) and Tompkins et al. (2021) in several respects. Rather than using fixed paths, many modern AGVs are freeranging, which means their preferred tracks are software programmed, and can be changed relatively easily when new stations or flows are added. A second difference is in the way they can be controlled. Agent technology allows decisions to be taken by these smart vehicles that in the past were taken by central controllers. This leads to adaptive, selflearning systems and is particularly appropriate for large, plex systems with many vehicles and much potential vehicle interference. These developments do not imply that the traditional decisionmaking problems bee obsolete. Rather, they lead to new challenges for research. We both discuss traditional AGVS’ decisionmaking problems and impacts of using freeranging AGVs on decisionmaking. 中英文資料 6 There are few review papers on AGV systems. However, they concentrate on only limited parts of the problem (Qiu et al. (2021) focus on scheduling and routing problems) or are not up to date (Co and Tanchoco, 1991。 King and Wilson, 1991。 Sinriech, 1995). Moreover, they ignore
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