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Learning-Based Control Strategies for Soft Robots: Theory, Achievements, and Future Challenges
IEEE Control Systems ( IF 5.7 ) Pub Date : 2023-05-25 , DOI: 10.1109/mcs.2023.3253421
Cecilia Laschi 1 , Thomas George Thuruthel 2 , Fumiya Lida 3 , Rochdi Merzouki 4 , Egidio Falotico 5
Affiliation  

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.

中文翻译:

基于学习的软体机器人控制策略:理论、成就和未来挑战

在过去的几十年里,软体机器人技术通过向刚性机器人世界引入新的柔顺体来挑战传统方法。这些技术和系统可以实现广泛的应用,包括人机交互和处理复杂环境。软体可以使其形状适应接触面,将应力分布到更大的区域,并增加接触表面积,从而减少冲击力。
更新日期:2023-05-26
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