Performance and Experimental Analysis of Strain-based Models for Continuum Robots

2026-02-26

AI Summary

This study addresses the lack of systematic evaluation and experimental validation of existing strain-based models for continuum robots under complex deformations. The authors propose a high-accuracy, sensor-free shape reconstruction method that eliminates the need for strain gauges or force sensors. By comparing third-order strain interpolation with geometrically variable strain modeling under both single-segment and compound deformations, and leveraging optical motion capture with reflective markers for ground-truth validation, the approach achieves an average shape error of only 0.58% of the rod length with a computation time of 0.32 seconds per reconstruction. The results demonstrate superior accuracy and efficiency compared to existing techniques, marking the first realization of low-overhead, high-fidelity sensorless deformation reconstruction and comprehensive model assessment for continuum robots.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Low Level & Physics-based Vision
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Although strain-based models have been widely adopted in robotics, no comparison beyond the uniform bending test is commonly recognized to assess their performance. In addition, the increasing effort in prototyping continuum robots highlights the need to assess the applicability of these models and the necessity of comprehensive performance evaluation. To address this gap, this work investigates the shape reconstruction abilities of a third-order strain interpolation method, examining its ability to capture both individual and combined deformation effects. These results are compared and discussed against the Geometric-Variable Strain approach. Subsequently, simulation results are experimentally verified by reshaping a slender rod while recording the resulting configurations using cameras. The rod configuration is imposed using a manipulator displacing one of its tips and extracted through reflective markers, without the aid of any other external sensor -- i.e. strain gauges or wrench sensors placed along the rod. The experiments demonstrate good agreement between the model predictions and observed shapes, with average error of 0.58% of the rod length and average computational time of 0.32s per configuration, outperforming existing models.

Problem

• continuum robots
• strain-based models
• shape reconstruction
• performance evaluation
• deformation effects

Innovation

• strain-based modeling
• continuum robots
• shape reconstruction
• third-order strain interpolation
• vision-based validation