A Model-Based Decoupling Strategy for Proprioception and Contact Sensing in an Architected Soft Manipulator
Robotics
Summary
The authors developed a way to help soft, bendable robots know their own shape and feel when they're touched using only air pressure sensors inside them. They used six air channels arranged in a special pattern and a mathematical model to figure out the robot's bending and detect when something presses on it. Their method worked well on one robot segment and also when multiple segments were combined into a longer soft robot arm, which could then do tasks like feeling objects and controlling force. This approach shows a practical way to add sensing abilities to soft robots without needing lots of different sensors.
Authors
Francesco Stella, Annan Zhang, Cosimo Della Santina, Josie Hughes, Daniela Rus
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.