提出多无人机协同巡检基准，评估异构系统规划能力。
Cooperative Aerial Robot Inspection Challenge: A Benchmark for Heterogeneous Multi-UAV Planning and Lessons Learned
- 构建含互补传感器的异构无人机团队仿真平台。
- 比赛验证了不同任务分配与路径规划策略的效果差异。
- 适合研究多机器人协同规划与智能算法的学者参考。
我们提出了协作空中机器人巡检挑战（CARIC），一个基于仿真的异构多无人机系统运动规划基准。CARIC包含具备互补传感器的无人机团队、真实约束条件以及以巡检质量和效率为核心的评估指标。该平台提供即用型感知-控制软件栈和多样化的任务场景，支持任务分配与运动规划算法的研发与评估。在IEEE CDC 2023和IROS 2024多机器人感知与导航工作坊上举办了基于CARIC的比赛，吸引了全球研究团队的创新方案。本文分析了CDC 2023前三名团队的探索、巡检及任务分配策略，并总结其在不同场景下的表现差异，揭示了该任务的复杂性，为未来协作式多无人机系统研究指明了方向。
原文摘要 · Abstract (English)
We propose the Cooperative Aerial Robot Inspection Challenge (CARIC), a simulation-based benchmark for motion planning algorithms in heterogeneous multi-UAV systems. CARIC features UAV teams with complementary sensors, realistic constraints, and evaluation metrics prioritizing inspection quality and efficiency. It offers a ready-to-use perception-control software stack and diverse scenarios to support the development and evaluation of task allocation and motion planning algorithms. Competitions using CARIC were held at IEEE CDC 2023 and the IROS 2024 Workshop on Multi-Robot Perception and Navigation, attracting innovative solutions from research teams worldwide. This paper examines the top three teams from CDC 2023, analyzing their exploration, inspection, and task allocation strategies while drawing insights into their performance across scenarios. The results highlight the task's complexity and suggest promising directions for future research in cooperative multi-UAV systems.
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