Robotics: Science and Systems XXII

Continuum Robot Localization using Distributed Time-of-Flight Sensors

Spencer Teetaert, Giammarco Caroleo, Marco Pontin, Sven Lilge, Jessica Burgner-Kahrs, Timothy Barfoot, Perla Maiolino

Abstract:

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.

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Bibtex:

  
@INPROCEEDINGS{TeetaertS-RSS-26, 
    AUTHOR    = {Spencer Teetaert AND Giammarco Caroleo AND Marco Pontin AND Sven Lilge AND Jessica Burgner-Kahrs AND Timothy Barfoot AND Perla Maiolino}, 
    TITLE     = {{Continuum Robot Localization using Distributed Time-of-Flight Sensors}}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2026}, 
    ADDRESS   = {Sydney, Australia}, 
    MONTH     = {July}, 
    DOI       = {10.15607/RSS.2026.XXII.050} 
}