204 citations · 401 across the 7 of their papers we have counts for
6 papers · 1 filter
Surrogate compliance modeling enables reinforcement learned locomotion gaits for soft robots
Jue Wang, Mingsong Jiang, Luis A. Ramirez +5
Adaptive morphogenetic robots adapt their morphology and control policies to meet changing tasks and environmental conditions. Many such systems leverage soft components, which ena…
Learning Differentiable Tensegrity Dynamics using Graph Neural Networks
Nelson Chen, Kun Wang, William R. Johnson +3
Tensegrity robots are composed of rigid struts and flexible cables. They constitute an emerging class of hybrid rigid-soft robotic systems and are promising systems for a wide arra…
Stretchable Arduinos embedded in soft robots
Stephanie J. Woodman, Dylan S. Shah, Melanie Landesberg +2
To achieve real-world functionality, robots must have the ability to carry out decision-making computations. However, soft robots stretch and therefore need a solution other than r…
Sustainably Grown: The Underdog Robots of the Future
Stoyan K. Smoukov
It is hard to imagine with the progress in robotics that current approaches are lacking somewhere, yet they will not be applicable to the majority of robots in the near future. We…
Soft Lattice Modules that Behave Independently and Collectively
Luyang Zhao, Yijia Wu, Julien Blanchet +5
Natural systems integrate the work of many sub-units (cells) toward a large-scale unified goal (morphological and behavioral), which can counteract the effects of unexpected experi…
A soft robot that adapts to environments through shape change
Dylan S. Shah, Joshua P. Powers, Liana G. Tilton +3
Many organisms, including various species of spiders and caterpillars, change their shape to switch gaits and adapt to different environments. Recent technological advances, rangin…