TY - GEN
T1 - Game-Theoretical MPC for Quadrotor Pursuit: Strategic Anticipation and Efficient Capture
AU - Ip, Chun Man Ben
AU - Lam, Yat Long
AU - Zhang, Chengchen
AU - Huang, Hailong
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/9
Y1 - 2025/9
N2 - This paper proposes a pursuit-centric Game-Theoretical MPC (GT-MPC) framework for quadrotors, lever-aging Nash equilibrium to anticipate evader maneuvers and optimize pursuit strategies. Unlike conventional MPC or reinforcement learning (RL) methods, GT-MPC explicitly models bidirectional adversarial interactions, enabling 63.03% faster average capture times in symmetric pursuit scenarios. By focusing on strategic parity - where pursuer and evader share identical dynamics - we demonstrate that superior decision-making, not hardware advantages, can also drive capture efficiency. Simulations across 50 randomized trials validate GT-MPC's robustness, with a 93% success rate under perfect information, outperforming state-of-the-art baseline.
AB - This paper proposes a pursuit-centric Game-Theoretical MPC (GT-MPC) framework for quadrotors, lever-aging Nash equilibrium to anticipate evader maneuvers and optimize pursuit strategies. Unlike conventional MPC or reinforcement learning (RL) methods, GT-MPC explicitly models bidirectional adversarial interactions, enabling 63.03% faster average capture times in symmetric pursuit scenarios. By focusing on strategic parity - where pursuer and evader share identical dynamics - we demonstrate that superior decision-making, not hardware advantages, can also drive capture efficiency. Simulations across 50 randomized trials validate GT-MPC's robustness, with a 93% success rate under perfect information, outperforming state-of-the-art baseline.
UR - https://www.scopus.com/pages/publications/105016129956
U2 - 10.1109/ICCA65672.2025.11129798
DO - 10.1109/ICCA65672.2025.11129798
M3 - Conference article published in proceeding or book
AN - SCOPUS:105016129956
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 552
EP - 557
BT - 2025 IEEE 19th International Conference on Control and Automation, ICCA 2025
PB - IEEE Computer Society
T2 - 19th IEEE International Conference on Control and Automation, ICCA 2025
Y2 - 30 June 2025 through 3 July 2025
ER -