Multi-Agent Path Finding (MAPF) is the problem of computing collision-free paths for a group of agents such that they can safely reach their target locations. In Multi-Agent Pickup and Delivery (MAPD), pickup and delivery locations are provided at runtime for an ideally ever-ending stream of tasks, making MAPD a combination between MAPF and online task assignment. Current models for MAPF and MAPD do not consider many of the practical issues encountered in real applications: in this paper, we present four new variants of the MAPF and MAPD problems we have recently devised which try to overcome different shortcomings of the original formulations. Promising directions of future work are also identified.

MAPF and MAPD: Recent Developments and Future Directions

Francesco Amigoni;Davide Azzalini;Benedetta Flammini
2022-01-01

Abstract

Multi-Agent Path Finding (MAPF) is the problem of computing collision-free paths for a group of agents such that they can safely reach their target locations. In Multi-Agent Pickup and Delivery (MAPD), pickup and delivery locations are provided at runtime for an ideally ever-ending stream of tasks, making MAPD a combination between MAPF and online task assignment. Current models for MAPF and MAPD do not consider many of the practical issues encountered in real applications: in this paper, we present four new variants of the MAPF and MAPD problems we have recently devised which try to overcome different shortcomings of the original formulations. Promising directions of future work are also identified.
2022
Proceedings of the AI*IA Workshop on Artificial Intelligence and Robotics (AIRO)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1232809
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