Closed-loop underwater soft robotic foil shape control using flexible e-skin

TL;DR

This paper introduces a novel method for real-time underwater shape estimation of soft robotic foils using flexible e-skin and machine learning, enabling precise closed-loop control without external sensors.

Contribution

It presents a new approach combining flexible capacitive e-skin and machine learning for real-time deformation measurement and control of underwater soft robots without external feedback.

Findings

Achieved accurate camber regulation with low RMS error.

Demonstrated effective shape tracking during sinusoidal and triangle actuation.

Measured tail tip deflection over a 30 mm range.

Abstract

The use of soft robotics for real-world underwater applications is limited, even more than in terrestrial applications, by the ability to accurately measure and control the deformation of the soft materials in real time without the need for feedback from an external sensor. Real-time underwater shape estimation would allow for accurate closed-loop control of soft propulsors, enabling high-performance swimming and manoeuvring. We propose and demonstrate a method for closed-loop underwater soft robotic foil control based on a flexible capacitive e-skin and machine learning which does not necessitate feedback from an external sensor. The underwater e-skin is applied to a highly flexible foil undergoing deformations from 2% to 9% of its camber by means of soft hydraulic actuators. Accurate set point regulation of the camber is successfully tracked during sinusoidal and triangle actuation routines with an amplitude of 5% peak-to-peak and 10-second period with a normalised RMS error of 0.11, and 2% peak-to-peak amplitude with a period of 5 seconds with a normalised RMS error of 0.03. The tail tip deflection can be measured across a 30 mm (0.15 chords) range. These results pave the way for using e-skin technology for underwater soft robotic closed-loop control applications.