DynORecon: Dynamic Object Reconstruction for Navigation
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913522847318016 |
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| author | Wang, Yiduo Morris, Jesse Wu, Lan Vidal-Calleja, Teresa Ila, Viorela |
| author_facet | Wang, Yiduo Morris, Jesse Wu, Lan Vidal-Calleja, Teresa Ila, Viorela |
| contents | This paper presents DynORecon, a Dynamic Object Reconstruction system that leverages the information provided by Dynamic SLAM to simultaneously generate a volumetric map of observed moving entities while estimating free space to support navigation. By capitalising on the motion estimations provided by Dynamic SLAM, DynORecon continuously refines the representation of dynamic objects to eliminate residual artefacts from past observations and incrementally reconstructs each object, seamlessly integrating new observations to capture previously unseen structures. Our system is highly efficient (~20 FPS) and produces accurate (~10 cm) reconstructions of dynamic objects using simulated and real-world outdoor datasets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_19928 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | DynORecon: Dynamic Object Reconstruction for Navigation Wang, Yiduo Morris, Jesse Wu, Lan Vidal-Calleja, Teresa Ila, Viorela Robotics This paper presents DynORecon, a Dynamic Object Reconstruction system that leverages the information provided by Dynamic SLAM to simultaneously generate a volumetric map of observed moving entities while estimating free space to support navigation. By capitalising on the motion estimations provided by Dynamic SLAM, DynORecon continuously refines the representation of dynamic objects to eliminate residual artefacts from past observations and incrementally reconstructs each object, seamlessly integrating new observations to capture previously unseen structures. Our system is highly efficient (~20 FPS) and produces accurate (~10 cm) reconstructions of dynamic objects using simulated and real-world outdoor datasets. |
| title | DynORecon: Dynamic Object Reconstruction for Navigation |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.19928 |