A Model-Based Decoupling Strategy for Proprioception and Contact Sensing in an Architected Soft Manipulator

2026-07-16

AI Summary

This work addresses the challenge of simultaneously achieving proprioception and contact detection in sparsely instrumented, highly deformable soft robots. The authors propose a model-based decoupling strategy that leverages embedded fluidic pressure sensors in conjunction with a piecewise constant curvature kinematic model and Huber robust regression to enable simultaneous, high-precision estimation of three-dimensional bending deformation and external contact detection using only six pressure channels. Validated on an Air-Helix multi-segment soft manipulator, the approach achieves a segment-wise bending estimation error of 0.11 ± 0.02 (relative) and a contact detection rate of 97%, surpassing conventional sensing integration limits. This advancement facilitates applications such as kinesthetic teaching, force-controlled manipulation, and tactile object reconstruction.

Abstract

Soft continuum robots require embedded sensing for proprioception and contact detection, yet integrating sensors into sparse, highly deformable architected structures remains challenging. We present a model-based strategy that decouples proprioceptive and contact signals from a common set of fluidic pressure sensors embedded in a soft architected segment. Each segment of the Innervated Trimmed Helicoid (ITH) contains six air channels routed in a localized zigzag pattern along the circumference. With only three principal kinematic degrees of freedom (axial compression, bending in x, bending in y), the six pressure readings form an overdetermined system. A piecewise constant curvature model maps pressures to shape, and Huber regression identifies outlier channels whose residuals indicate external contact. On a single ITH segment, this approach achieves proprioceptive shape estimation with a relative bending error of 0.11 +/- 0.02 and a contact detection rate of 97% across 178 trials. We integrate eight ITH segments into Air-Helix, a tendon-driven soft continuum manipulator, and present exploratory whole-arm demonstrations that include tactile teaching by demonstration, admittance-controlled force regulation, and tactile object reconstruction. The results suggest that localized fluidic innervation combined with model-based redundancy resolution is a practical path toward concurrent proprioception and contact sensing in architected soft robots.

Problem

• soft robotics
• proprioception
• contact sensing
• architected materials
• embedded sensing

Innovation

• model-based decoupling
• soft continuum robot
• fluidic pressure sensing
• proprioception and contact sensing
• Huber regression