A Cooperative-Competitive Strategy for Autonomous Multidrone Racing

Autonomous multidrone racing is extremely challenging due to rich agent interactions and cluttered environments. Although there has been some progress, existing approaches often do not properly consider cooperative behavior among drones and are computationally expensive, deteriorating the racing performance. To address these issues, we propose a novel cooperative-competitive strategy based on the leader-wingman framework for autonomous multidrone racing. For the leader, a game-theoretic method is designed to compete against the opponent. For the wingman, a novel line of sight-based cooperative method is proposed to support the leader by blocking the opponent. As a result, the win rate can be improved even when the opponent has a significant speed advantage. Furthermore, our strategy has a lower computational cost than the existing game-based strategies. Finally, we verify our strategy by extensive comparison to the state-of-the-art strategy in simulation and in the physical world.