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.

翻译：我们提出了协同空中机器人巡检挑战（CARIC），这是一个面向异构多无人机系统运动规划算法的仿真基准。CARIC具备配备互补传感器的无人机编队、真实的约束条件，以及优先考虑巡检质量与效率的评价指标。它提供了一套即用型感知-控制软件栈和多样化的场景，以支持任务分配与运动规划算法的开发与评估。基于CARIC的竞赛已在IEEE CDC 2023和IROS 2024多机器人感知与导航研讨会上举办，吸引了全球研究团队的创新解决方案。本文分析了CDC 2023的前三名团队，剖析了其探索、巡检与任务分配策略，并总结了他们在不同场景下的性能表现。结果凸显了该任务的复杂性，并为协同多无人机系统的未来研究指出了有前景的方向。