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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.12362 |
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| _version_ | 1866909351944388608 |
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| author | Zimmerman, Nicky Sodano, Matteo |
| author_facet | Zimmerman, Nicky Sodano, Matteo |
| contents | Lifelong localization is crucial for enabling the autonomy of service robots. In this paper, we present an overview of our past research on long-term localization and mapping, exploiting geometric priors such as floor plans and integrating textual and semantic information. Our approach was validated on challenging sequences spanning over many months, and we released open source implementations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_12362 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Human-Inspired Long-Term Indoor Localization in Human-Oriented Environment Zimmerman, Nicky Sodano, Matteo Robotics Lifelong localization is crucial for enabling the autonomy of service robots. In this paper, we present an overview of our past research on long-term localization and mapping, exploiting geometric priors such as floor plans and integrating textual and semantic information. Our approach was validated on challenging sequences spanning over many months, and we released open source implementations. |
| title | Human-Inspired Long-Term Indoor Localization in Human-Oriented Environment |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.12362 |