Electronic skins and machine learning for intelligent soft robots

Soft robots have garnered interest for real-world applications because of their intrinsic safety embedded at the material level. These robots use deformable materials capable of shape and behavioral changes and allow conformable physical contact for manipulation. Yet, with the introduction of soft a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Science robotics Jg. 5; H. 41
Hauptverfasser: Shih, Benjamin, Shah, Dylan, Li, Jinxing, Thuruthel, Thomas G, Park, Yong-Lae, Iida, Fumiya, Bao, Zhenan, Kramer-Bottiglio, Rebecca, Tolley, Michael T
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 22.04.2020
Schlagworte:
Biomechanical Phenomena
Biomimetics - instrumentation
Biomimetics - statistics & numerical data
Equipment Design
Feedback, Sensory - physiology
Humans
Machine Learning - trends
Robotics - instrumentation
Robotics - statistics & numerical data
Robotics - trends
Skin - anatomy & histology
Skin Physiological Phenomena
Touch - physiology
Wearable Electronic Devices - trends
ISSN:2470-9476, 2470-9476
Online-Zugang:Weitere Angaben
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Soft robots have garnered interest for real-world applications because of their intrinsic safety embedded at the material level. These robots use deformable materials capable of shape and behavioral changes and allow conformable physical contact for manipulation. Yet, with the introduction of soft and stretchable materials to robotic systems comes a myriad of challenges for sensor integration, including multimodal sensing capable of stretching, embedment of high-resolution but large-area sensor arrays, and sensor fusion with an increasing volume of data. This Review explores the emerging confluence of e-skins and machine learning, with a focus on how roboticists can combine recent developments from the two fields to build autonomous, deployable soft robots, integrated with capabilities for informative touch and proprioception to stand up to the challenges of real-world environments.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
ISSN:2470-9476
2470-9476
DOI:10.1126/scirobotics.aaz9239