A Generalized Potential Game Approach of UAV Swarm Coordination for Hidden Target Localization
Year: 2025
Type: article
Abstract: Considering a swarm of Unmanned Aerial Vehicles (UAVs) carrying sensors with nondeterministic detection and noisy localization measurements, while sharing observations with neighboring UAVs, we address the problem of localization of a hidden target in continuous space and discrete time. The goal is to coordinate UAVs to maximize the information gathered while minimizing their individual energy costs. We formulate the problem as a time-varying non-cooperative game with coupling constraints. We show that the target is localized in finite time with probability one and that the game has a generalized potential structure. Further, we provide an exact best-response algorithm for UAVs to iteratively compute their trajectories. Finally, we numerically compare the potential game to the team-based approach, demonstrating comparable performance under different communication graph structures and assessing the impact of the swarm size on various metrics.
Source: IEEE Control Systems Letters
Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Université de Lille, Centre de Recherche en Informatique, Signal et Automatique de Lille, INOCS: Optimisation intégrée pour problèmes à structure complexe, Centrale Lille Institut, École nationale des ponts et chaussées, Institut Polytechnique de Paris
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Ministère des Armées
OpenAlex ID: W4414566775
FWCI:
Cites:
Cited by:
Related to: