Cooperative Aerial Robot Inspection Challenge: A Benchmark for Heterogeneous Multi-UAV Planning and Lessons Learned
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| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866929674844635136 |
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| author | Cao, Muqing Nguyen, Thien-Minh Yuan, Shenghai Anastasiou, Andreas Zacharia, Angelos Papaioannou, Savvas Kolios, Panayiotis Panayiotou, Christos G. Polycarpou, Marios M. Xu, Xinhang Zhang, Mingjie Gao, Fei Zhou, Boyu Chen, Ben M. Xie, Lihua |
| author_facet | Cao, Muqing Nguyen, Thien-Minh Yuan, Shenghai Anastasiou, Andreas Zacharia, Angelos Papaioannou, Savvas Kolios, Panayiotis Panayiotou, Christos G. Polycarpou, Marios M. Xu, Xinhang Zhang, Mingjie Gao, Fei Zhou, Boyu Chen, Ben M. Xie, Lihua |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_06566 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cooperative Aerial Robot Inspection Challenge: A Benchmark for Heterogeneous Multi-UAV Planning and Lessons Learned Cao, Muqing Nguyen, Thien-Minh Yuan, Shenghai Anastasiou, Andreas Zacharia, Angelos Papaioannou, Savvas Kolios, Panayiotis Panayiotou, Christos G. Polycarpou, Marios M. Xu, Xinhang Zhang, Mingjie Gao, Fei Zhou, Boyu Chen, Ben M. Xie, Lihua Robotics Systems and Control 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. |
| title | Cooperative Aerial Robot Inspection Challenge: A Benchmark for Heterogeneous Multi-UAV Planning and Lessons Learned |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2501.06566 |