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Learning-Based Control Strategies for Soft Robots: Theory, Achievements, and Future Challenges | IEEE Journals & Magazine | IEEE Xplore

Learning-Based Control Strategies for Soft Robots: Theory, Achievements, and Future Challenges


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 techn...Show More

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.
Published in: IEEE Control Systems Magazine ( Volume: 43, Issue: 3, June 2023)
Page(s): 100 - 113
Date of Publication: 25 May 2023

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