Sliding Sensors: Configurable Confidence in State Estimation for Continuum Robots

2026-08-05

AI Summary

This work addresses the spatially non-uniform confidence in state estimation for continuum robots operating in uncertain environments, which compromises accuracy in task-critical regions. To overcome this limitation, the authors propose a mechanically reconfigurable sensing mechanism that introduces an embedded sensor capable of longitudinal sliding along the robot’s body. By dynamically adjusting the sensor’s position, the method actively shapes the spatial distribution of estimation uncertainty, breaking away from the constraints of conventional fixed-sensor layouts. This enables co-optimization of sensor configuration and estimation confidence. Experimental results demonstrate that, compared to a single end-fixed sensor, the proposed reciprocating sliding strategy significantly reduces whole-body shape estimation error over time and effectively enhances estimation confidence in critical regions.

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.

Problem

• continuum robots
• state estimation
• uncertainty
• spatially non-uniform
• confidence

Innovation

• sliding sensors
• continuum robots
• state estimation
• uncertainty shaping
• reconfigurable sensing