Capability-aware Task Allocation and Team Formation Analysis for Cooperative Exploration of Complex Environments
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913569623244800 |
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| author | Ginting, Muhammad Fadhil Otsu, Kyohei Kochenderfer, Mykel J. Agha-mohammadi, Ali-akbar |
| author_facet | Ginting, Muhammad Fadhil Otsu, Kyohei Kochenderfer, Mykel J. Agha-mohammadi, Ali-akbar |
| contents | To achieve autonomy in complex real-world exploration missions, we consider deployment strategies for a team of robots with heterogeneous autonomy capabilities. In this work, we formulate a multi-robot exploration mission and compute an operation policy to maintain robot team productivity and maximize mission rewards. The environment description, robot capability, and mission outcome are modeled as a Markov decision process (MDP). We also include constraints in real-world operation, such as sensor failures, limited communication coverage, and mobility-stressing elements. Then, we study the proposed operation model on a real-world scenario in the context of the DARPA Subterranean (SubT) Challenge. The computed deployment policy is also compared against the human-based operation strategy in the final competition of the SubT Challenge. Finally, using the proposed model, we discuss the design trade-off on building a multi-robot team with heterogeneous capabilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_00400 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Capability-aware Task Allocation and Team Formation Analysis for Cooperative Exploration of Complex Environments Ginting, Muhammad Fadhil Otsu, Kyohei Kochenderfer, Mykel J. Agha-mohammadi, Ali-akbar Robotics To achieve autonomy in complex real-world exploration missions, we consider deployment strategies for a team of robots with heterogeneous autonomy capabilities. In this work, we formulate a multi-robot exploration mission and compute an operation policy to maintain robot team productivity and maximize mission rewards. The environment description, robot capability, and mission outcome are modeled as a Markov decision process (MDP). We also include constraints in real-world operation, such as sensor failures, limited communication coverage, and mobility-stressing elements. Then, we study the proposed operation model on a real-world scenario in the context of the DARPA Subterranean (SubT) Challenge. The computed deployment policy is also compared against the human-based operation strategy in the final competition of the SubT Challenge. Finally, using the proposed model, we discuss the design trade-off on building a multi-robot team with heterogeneous capabilities. |
| title | Capability-aware Task Allocation and Team Formation Analysis for Cooperative Exploration of Complex Environments |
| topic | Robotics |
| url | https://arxiv.org/abs/2411.00400 |