Autonomous Multi-Robot Exploration Strategies for 3D Environments with Fire Detection Capabilitie
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910712729698304 |
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| author | Shaw, Ankit |
| author_facet | Shaw, Ankit |
| contents | This paper presents a comprehensive overview of exploration strategies utilized in both 2D and 3D environments, focusing on autonomous multi-robot systems designed for building exploration and fire detection. We explore the limitations of traditional algorithms that rely on prior knowledge and predefined maps, emphasizing the challenges faced when environments undergo changes that invalidate these maps. Our modular approach integrates localization, mapping, and trajectory planning to facilitate effective exploration using an OctoMap framework generated from point cloud data. The exploration strategy incorporates obstacle avoidance through potential fields, ensuring safe navigation in dynamic settings. Additionally, I propose future research directions, including decentralized map creation, coordinated exploration among unmanned aerial vehicles (UAVs), and adaptations to time-varying environments. This work serves as a foundation for advancing coordinated multi-robot exploration algorithms, enhancing their applicability in real-world scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_15953 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Autonomous Multi-Robot Exploration Strategies for 3D Environments with Fire Detection Capabilitie Shaw, Ankit Robotics This paper presents a comprehensive overview of exploration strategies utilized in both 2D and 3D environments, focusing on autonomous multi-robot systems designed for building exploration and fire detection. We explore the limitations of traditional algorithms that rely on prior knowledge and predefined maps, emphasizing the challenges faced when environments undergo changes that invalidate these maps. Our modular approach integrates localization, mapping, and trajectory planning to facilitate effective exploration using an OctoMap framework generated from point cloud data. The exploration strategy incorporates obstacle avoidance through potential fields, ensuring safe navigation in dynamic settings. Additionally, I propose future research directions, including decentralized map creation, coordinated exploration among unmanned aerial vehicles (UAVs), and adaptations to time-varying environments. This work serves as a foundation for advancing coordinated multi-robot exploration algorithms, enhancing their applicability in real-world scenarios. |
| title | Autonomous Multi-Robot Exploration Strategies for 3D Environments with Fire Detection Capabilitie |
| topic | Robotics |
| url | https://arxiv.org/abs/2411.15953 |