Optically Sensorized Electro-Ribbon Actuator (OS-ERA)

TL;DR

This paper introduces OS-ERA, an optically sensorized electro-ribbon actuator that uses embedded soft optical waveguides and machine learning to achieve high-fidelity, fast, and repeatable bending state classification, enabling closed-loop control.

Contribution

The paper presents a novel optical sensing solution for ERAs that improves accuracy and speed of proprioception without affecting actuation, advancing closed-loop control capabilities.

Findings

High classification accuracy of bending states

Robustness to actuation speed variations

Reliable and repeatable sensing signals

Abstract

Electro-Ribbon Actuators (ERAs) are lightweight flexural actuators that exhibit ultrahigh displacement and fast movement. However, their embedded sensing relies on capacitive sensors with limited precision, which hinders accurate control. We introduce OS-ERA, an optically sensorized ERA that yields reliable proprioceptive information, and we focus on the design and integration of a sensing solution without affecting actuation. To analyse the complex curvature of an ERA in motion, we design and embed two soft optical waveguide sensors. A classifier is trained to map the sensing signals in order to distinguish eight bending states. We validate our model on six held-out trials and compare it against signals' trajectories learned from training runs. Across all tests, the sensing output signals follow the training manifold, and the predicted sequence mirrors real performance and confirms repeatability. Despite deliberate train-test mismatches in actuation speed, the signal trajectories preserve their shape, and classification remains consistently accurate, demonstrating practical voltage- and speed-invariance. As a result, OS-ERA classifies bending states with high fidelity; it is fast and repeatable, solving a longstanding bottleneck of the ERA, enabling steps toward closed-loop control.