Editorial: Machine Learning Techniques for Soft Robots.
View / Open Files
Publication Date
2021Journal Title
Front Robot AI
ISSN
2296-9144
Publisher
Frontiers Media SA
Volume
8
Pages
726774
Language
eng
Type
Article
This Version
VoR
Physical Medium
Electronic-eCollection
Metadata
Show full item recordCitation
George Thuruthel, T., Falotico, E., Beccai, L., & Iida, F. (2021). Editorial: Machine Learning Techniques for Soft Robots.. Front Robot AI, 8 726774. https://doi.org/10.3389/frobt.2021.726774
Keywords
editorial, machine learning, modeling and control, soft robotics, soft sensing
Sponsorship
European Commission Horizon 2020 (H2020) Future and Emerging Technologies (FET) (828818)
Identifiers
External DOI: https://doi.org/10.3389/frobt.2021.726774
This record's URL: https://www.repository.cam.ac.uk/handle/1810/327932
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk