Laschi, Cecilia;
George Thuruthel, Thomas;
Lida, Fumiya;
Merzouki, Rochdi;
Falotico, Egidio;
(2023)
Learning-Based Control Strategies for Soft Robots: Theory, Achievements, and Future Challenges.
IEEE Control Systems
, 43
(3)
pp. 100-113.
10.1109/mcs.2023.3253421.
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Abstract
In the last few decades, soft robotics technologies have challenged conventional approaches by introducing new, compliant bodies to the world of rigid robots. These technologies and systems may enable a wide range of applications, including human-robot interaction and dealing with complex environments. Soft bodies can adapt their shape to contact surfaces, distribute stress over a larger area, and increase the contact surface area, thus reducing impact forces.
| Type: | Article |
|---|---|
| Title: | Learning-Based Control Strategies for Soft Robots: Theory, Achievements, and Future Challenges |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/mcs.2023.3253421 |
| Publisher version: | https://doi.org/10.1109/mcs.2023.3253421 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Damping, Surface impedance, Surface morphology, Soft robotics, Stability analysis, Safety, Observability |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10172458 |
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