Home // International Journal On Advances in Systems and Measurements, volume 18, numbers 1 and 2, 2025 // View article
Authors:
Juliette Grosset
Alain-Jérôme Fougères
Moïse Djoko-Kouam
Jean-Marie Bonnin
Keywords: autonomous industrial vehicle; dynamic task allocation; collision avoidance; V2X cooperation; fuzzy agent; agent-based simulation; Airport 4.0.
Abstract:
The paper presents a multi-agent simulation using fuzzy inference to explore the task allocation, collision avoidance, and battery charging management of mobile baggage conveyor robots in an airport, in an integrated way. The approach leverages V2X cooperation to enable real-time communication between mobile robots and airport infrastructure, enhancing adaptability thanks to a distributed system, adapting to variations in the availability of conveyor agents, their battery capacity, infrastructure resource availability, and awareness of the activity of the conveyor fleet. Dynamic factors, such as workload variations and communication between the conveyor agents and infrastructure are considered as heuristics, highlighting the importance of flexible and collaborative approaches in autonomous systems. The results highlight the effectiveness of adaptive fuzzy multi-agent models to optimize dynamic task allocation, adapt to the variation of baggage arrival flows, improve the overall operational efficiency of conveyor agents, and collision avoidance, and reduce their energy consumption through V2X-enabled cooperation.
Pages: 8 to 18
Copyright: Copyright (c) to authors, 2025. Used with permission.
Publication date: June 30, 2025
Published in: journal
ISSN: 1942-261x