SafeSwarm: 密集群衆下で着陸するドローン群のための分散安全強化学習
SafeSwarm: Decentralized Safe RL for the Swarm of Drones Landing in Dense Crowds
安全学習と強化学習を組み合わせ、障害物や機体間の衝突を避けながら移動する着陸パッドへ群れで着陸する分散制御を実現し、実機実験で高精度・無衝突着陸を示した。
著者: Grik Tadevosyan, Maksim Osipenko, Demetros Aschu, Aleksey Fedoseev, Valerii Serpiva, Oleg Sautenkov, Sausar Karaf, Dzmitry Tsetserukou
分類: cs.RO
原文アブストラクト
This paper introduces a safe swarm of drones capable of performing landings in crowded environments robustly by relying on Reinforcement Learning techniques combined with Safe Learning. The developed system allows us to teach the swarm of drones with different dynamics to land on moving landing pads in an environment while avoiding collisions with obstacles and between agents. The safe barrier net algorithm was developed and evaluated using a swarm of Crazyflie 2.1 micro quadrotors, which were tested indoors with the Vicon motion capture system to ensure precise localization and control. Experimental results show that our system achieves landing accuracy of 2.25 cm with a mean time of 17 s and collision-free landings, underscoring its effectiveness and robustness in real-world scenarios. This work offers a promising foundation for applications in environments where safety and precision are paramount.
