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Optimal Planning of Routes, Schedules, and Charging Times of Automated Guided Electric Vehicles

Title: Optimal Planning of Routes, Schedules, and Charging Times of Automated Guided Electric Vehicles
Authors: Botond Bertok; Márton Frits; Károly Kalauz; Petar Sabev Varbanov
Source: Energies ; Volume 19 ; Issue 3 ; Pages: 813
Publisher Information: Multidisciplinary Digital Publishing Institute
Publication Year: 2026
Collection: MDPI Open Access Publishing
Subject Terms: automated guided vehicle; minimal energy demand; scheduling; P-graph; trajectory
Description: In traditional industry setups, Automated Guided Vehicles (AGVs) follow trajectories planned together with the layout of the storage or production facility and supported by fixed markers on the floor or on the walls. Traffic rules manage the avoidance of multiple vehicles, while fleet management gets movement and transportation commands completed as soon as possible. In contrast, recent developments in navigation and advanced computing, sensor, and communication capabilities make their free movement safe and manageable. Detailed route planning and scheduling can guarantee that the vehicles keep a safe distance in time and space. A recent challenge of electric AGVs is that their charging may take several hours, which must be factored into their schedule. This has made minimal energy demand a key objective alongside earliest delivery and strictly meeting the deadlines. This paper presents a method for detailed routing and scheduling of AGV fleets to minimize energy consumption while considering battery levels and charging times. The optimization method is illustrated by a case study where multiple delivery tasks are performed by synchronized movement of vehicles on a complex warehouse layout. In the optimal solution, the scheduled waiting times for collision avoidance are utilized by the vehicles to pre-charge their batteries.
Document Type: text
File Description: application/pdf
Language: English
Relation: E: Electric Vehicles; https://dx.doi.org/10.3390/en19030813
DOI: 10.3390/en19030813
Availability: https://doi.org/10.3390/en19030813
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.9BA61B5C
Database: BASE