A Game-Theoretic MPC Planner for Cooperative and Adversarial Drone Coordination
A Game-Theoretic MPC Planner for Cooperative and Adversarial Drone Coordination
This paper introduces and evaluates a game-theoretic model predictive control (MPC) planner designed for cooperative goal reaching and adversarial pursuit-evasion tasks using drones.
The study presents a game-theoretic model predictive control planner validated via PyBullet simulations and a single laboratory flight, with computational limits identified for real-time planning under varying drone counts and prediction horizons.
Source: arXiv Robotics — research abstracts · Read original article ↗
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nfigurations. PyBullet simulations demonstrate cooperative goal reaching and pursuit-evasion. A laboratory flight complements the simulations by validating the trajectory-tracking interfaces on physical drones. The planner can serve as a basis for further evaluation and controller development.
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arXiv:2611.12226v1 Announce Type: new Abstract: We present and evaluate a game-theoretic model predictive control planner for cooperative goal reaching and adversarial pursuit-evasion with drones. The planner combines 3D prediction, individual objectives, optional shared separation constraints and trajectory-tracking interfaces. A comparison of cooperative game solvers assesses their ability to find feasible trajecto
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Source：arXiv Robotics — research abstracts · arxiv.org