AT-Drone: Benchmarking Adaptive Teaming in Multi-Drone Pursuit

• URL: http://arxiv.org/abs/2502.09762v2
• Date: Fri, 02 May 2025 10:33:06 GMT
• Title: AT-Drone: Benchmarking Adaptive Teaming in Multi-Drone Pursuit
• Authors: Yang Li, Junfan Chen, Feng Xue, Jiabin Qiu, Wenbin Li, Qingrui Zhang, Ying Wen, Wei Pan,
• Abstract summary: AT-Drone is the first benchmark explicitly designed to facilitate comprehensive training and evaluation of adaptive teaming strategies in multi-drone pursuit scenarios.<n>A streamlined real-world deployment pipeline translates simulation insights into practical drone evaluations using edge devices and Crazyflie drones.<n>Four progressively challenging multi-drone pursuit scenarios confirm AT-Drone's effectiveness in advancing adaptive teaming research.
• Score: 23.110351678527017
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Adaptive teaming-the capability of agents to effectively collaborate with unfamiliar teammates without prior coordination-is widely explored in virtual video games but overlooked in real-world multi-robot contexts. Yet, such adaptive collaboration is crucial for real-world applications, including border surveillance, search-and-rescue, and counter-terrorism operations. To address this gap, we introduce AT-Drone, the first dedicated benchmark explicitly designed to facilitate comprehensive training and evaluation of adaptive teaming strategies in multi-drone pursuit scenarios. AT-Drone makes the following key contributions: (1) An adaptable simulation environment configurator that enables intuitive and rapid setup of adaptive teaming multi-drone pursuit tasks, including four predefined pursuit environments. (2) A streamlined real-world deployment pipeline that seamlessly translates simulation insights into practical drone evaluations using edge devices and Crazyflie drones. (3) A novel algorithm zoo integrated with a distributed training framework, featuring diverse algorithms explicitly tailored, for the first time, to multi-pursuer and multi-evader settings. (4) Standardized evaluation protocols with newly designed unseen drone zoos, explicitly designed to rigorously assess the performance of adaptive teaming. Comprehensive experimental evaluations across four progressively challenging multi-drone pursuit scenarios confirm AT-Drone's effectiveness in advancing adaptive teaming research. Real-world drone experiments further validate its practical feasibility and utility for realistic robotic operations. Videos, code and weights are available at \url{https://sites.google.com/view/at-drone}.

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