A Flow Based Planning Method for Multi-Agent Progression with Deployable Agents and Communication Constraints

Authors

  • Emile Siboulet Safran Electronics & Defense, Massy, France LAAS-CNRS, Université de Toulouse, CNRS, INSA, Toulouse, France
  • Roland Godet ONERA/DTIS, Université de Toulouse, France LAAS-CNRS, Université de Toulouse, CNRS, INSA, Toulouse, France
  • Arthur Bit-Monnot LAAS-CNRS, Université de Toulouse, CNRS, INSA, Toulouse, France
  • Marc-Emmanuel Coupvent Des Graviers Safran Electronics & Defense, Massy, France
  • Christophe Guettier Safran Electronics & Defense, Massy, France
  • Simon Lacroix LAAS-CNRS, Université de Toulouse, CNRS, INSA, Toulouse, France

DOI:

https://doi.org/10.1609/icaps.v35i1.36137

Abstract

This paper deals with the problem of planning multiple agent movements through a mission area modeled as a graph. The agents undergo classic communication and temporal constraints, and the quantitative objective is the minimization of the team’s traversal makespan. Additional specificities make the problem a particularly complex routing one: on some nodes are associated durative and coordinated actions to perform, which can involve either the co-presence of several agents or time dependencies. Also, some agents are deployable and able to move on denser graphs: namely, aerial robots can take off and land on the ground vehicle at any planned position, and can fly above ground obstacles. We model the problem as a CSP and solve it with a network flow model. Results show the efficacy of the model and resolution scheme, which provides solutions with one or two orders of magnitude smaller time than a numerical temporal hierarchical planning model, with only a few percent loss of optimality.

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Published

2025-09-16

How to Cite

Siboulet, E., Godet, R., Bit-Monnot, A., Graviers, M.-E. C. D., Guettier, C., & Lacroix, S. (2025). A Flow Based Planning Method for Multi-Agent Progression with Deployable Agents and Communication Constraints. Proceedings of the International Conference on Automated Planning and Scheduling, 35(1), 348-357. https://doi.org/10.1609/icaps.v35i1.36137