English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Untethered soft robots that locomote using electrothermally-responsivematerials like shape memory alloy (SMA) face challenging design constraints forsensing actuator states. At the same time, modeling of actuator behaviors facessteep challenges, even with available sensor data, due to complexelectrical-thermal-mechanical interactions and hysteresis. This articleproposes a framework for in-situ sensing and dynamics modeling of actuatorstates, particularly temperature of SMA wires, which is used to predict robotmotions. A planar soft limb is developed, actuated by a pair of SMA coils, thatincludes compact and robust sensors for temperature and angular deflection.Data from these sensors are used to train a neural network based on the longshort-term memory (LSTM) architecture to model both unidirectional (single SMA)and bidirectional (both SMAs) motion. Predictions from the model demonstratethat data from the temperature sensor, combined with control inputs, allow fordynamics predictions over extraordinarily long open-loop timescales (10minutes) with little drift. Prediction errors are on the order of the softdeflection sensor's accuracy. This architecture allows for compact designs ofelectrothermally-actuated soft robots that include sensing sufficient formotion predictions, helping to bring these robots into practical application.

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs