Mobile Robot Localization: a Modular, Odometry-Improving Approach
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916168048050176 |
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| author | Mozzarelli, Luca Cattaneo, Luca Corno, Matteo Savaresi, Sergio Matteo |
| author_facet | Mozzarelli, Luca Cattaneo, Luca Corno, Matteo Savaresi, Sergio Matteo |
| contents | Despite the number of works published in recent years, vehicle localization remains an open, challenging problem. While map-based localization and SLAM algorithms are getting better and better, they remain a single point of failure in typical localization pipelines. This paper proposes a modular localization architecture that fuses sensor measurements with the outputs of off-the-shelf localization algorithms. The fusion filter estimates model uncertainties to improve odometry in case absolute pose measurements are lost entirely. The architecture is validated experimentally on a real robot navigating autonomously proving a reduction of the position error of more than 90% with respect to the odometrical estimate without uncertainty estimation in a two-minute navigation period without position measurements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_13452 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Mobile Robot Localization: a Modular, Odometry-Improving Approach Mozzarelli, Luca Cattaneo, Luca Corno, Matteo Savaresi, Sergio Matteo Robotics Despite the number of works published in recent years, vehicle localization remains an open, challenging problem. While map-based localization and SLAM algorithms are getting better and better, they remain a single point of failure in typical localization pipelines. This paper proposes a modular localization architecture that fuses sensor measurements with the outputs of off-the-shelf localization algorithms. The fusion filter estimates model uncertainties to improve odometry in case absolute pose measurements are lost entirely. The architecture is validated experimentally on a real robot navigating autonomously proving a reduction of the position error of more than 90% with respect to the odometrical estimate without uncertainty estimation in a two-minute navigation period without position measurements. |
| title | Mobile Robot Localization: a Modular, Odometry-Improving Approach |
| topic | Robotics |
| url | https://arxiv.org/abs/2403.13452 |