Continuum Robot Localization using Distributed Time-of-Flight Sensors
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866917473774731264 |
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| author | Teetaert, Spencer Caroleo, Giammarco Pontin, Marco Lilge, Sven Burgner-Kahrs, Jessica Barfoot, Timothy D. Maiolino, Perla |
| author_facet | Teetaert, Spencer Caroleo, Giammarco Pontin, Marco Lilge, Sven Burgner-Kahrs, Jessica Barfoot, Timothy D. Maiolino, Perla |
| contents | Localization and mapping of an environment are crucial tasks for any robot operating in unstructured environments. Time-of-flight (ToF) sensors (e.g.,~lidar) have proven useful in mobile robotics, where high-resolution sensors can be used for simultaneous localization and mapping. In soft and continuum robotics, however, these high-resolution sensors are too large for practical use. This, combined with the deformable nature of such robots, has resulted in continuum robot (CR) localization and mapping in unstructured environments being a largely untouched area. In this work, we present a localization technique for CRs that relies on small, low-resolution ToF sensors distributed along the length of the robot. By fusing measurement information with a robot shape prior, we show that accurate localization is possible despite each sensor experiencing frequent degenerate scenarios. We achieve an average localization error of 2.5cm in position and 7.2° in rotation across all experimental conditions with a 53cm long robot. We demonstrate that the results are repeated across multiple environments, in both simulation and real-world experiments, and study robustness in the estimation to deviations in the prior map. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_07209 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Continuum Robot Localization using Distributed Time-of-Flight Sensors Teetaert, Spencer Caroleo, Giammarco Pontin, Marco Lilge, Sven Burgner-Kahrs, Jessica Barfoot, Timothy D. Maiolino, Perla Robotics Localization and mapping of an environment are crucial tasks for any robot operating in unstructured environments. Time-of-flight (ToF) sensors (e.g.,~lidar) have proven useful in mobile robotics, where high-resolution sensors can be used for simultaneous localization and mapping. In soft and continuum robotics, however, these high-resolution sensors are too large for practical use. This, combined with the deformable nature of such robots, has resulted in continuum robot (CR) localization and mapping in unstructured environments being a largely untouched area. In this work, we present a localization technique for CRs that relies on small, low-resolution ToF sensors distributed along the length of the robot. By fusing measurement information with a robot shape prior, we show that accurate localization is possible despite each sensor experiencing frequent degenerate scenarios. We achieve an average localization error of 2.5cm in position and 7.2° in rotation across all experimental conditions with a 53cm long robot. We demonstrate that the results are repeated across multiple environments, in both simulation and real-world experiments, and study robustness in the estimation to deviations in the prior map. |
| title | Continuum Robot Localization using Distributed Time-of-Flight Sensors |
| topic | Robotics |
| url | https://arxiv.org/abs/2602.07209 |