Sliding Sensors: Configurable Confidence in State Estimation for Continuum Robots
arXiv:2608.05410v1 Announce Type: new Abstract: Continuum robots often operate in uncertain environments, where accurate state estimation is essential for safe interactions. Estimate uncertainty is inherently spatially non-uniform: confidence varies depending on where measurements are available. Global estimation accuracy is not always the top priority, but rather achieving sufficient confidence at task-relevant locations along the robot. This extended abstract introduces mechanically reconfigurable sensing enabling uncertainty-shaping in state estimation for continuum robots. We present a concept hardware design demonstrating the feasibility of longitudinal translation of a sensor within a continuum robot. We demonstrate that state estimation confidence can be reconfigured by varying the sensor location, and show a reduction of full-body shape estimation errors when sliding the sensor back and forth over time, compared to a single fixed tip sensor.
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[Submitted on 5 Aug 2026]
Title:Sliding Sensors: Configurable Confidence in State Estimation for Continuum Robots
View a PDF of the paper titled Sliding Sensors: Configurable Confidence in State Estimation for Continuum Robots, by Ella Walsh and 4 other authors
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Abstract:Continuum robots often operate in uncertain environments, where accurate state estimation is essential for safe interactions. Estimate uncertainty is inherently spatially non-uniform: confidence varies depending on where measurements are available. Global estimation accuracy is not always the top priority, but rather achieving sufficient confidence at task-relevant locations along the robot. This extended abstract introduces mechanically reconfigurable sensing enabling uncertainty-shaping in state estimation for continuum robots. We present a concept hardware design demonstrating the feasibility of longitudinal translation of a sensor within a continuum robot. We demonstrate that state estimation confidence can be reconfigured by varying the sensor location, and show a reduction of full-body shape estimation errors when sliding the sensor back and forth over time, compared to a single fixed tip sensor.
Comments: Accepted as an extended abstract at 2026 IEEE 9th International Conference on Soft Robotics (RoboSoft). * Equal contribution
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2608.05410 [cs.RO]
(or arXiv:2608.05410v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2608.05410
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Spencer Teetaert [view email] [v1] Wed, 5 Aug 2026 21:05:25 UTC (525 KB)
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