An overview of soft robotics

O Yasa, Y Toshimitsu, MY Michelis… - Annual Review of …, 2023 - annualreviews.org
Soft robots' flexibility and compliance give them the potential to outperform traditional rigid-
bodied robots while performing multiple tasks in unexpectedly changing environments and …

Soft pneumatic actuators: A review of design, fabrication, modeling, sensing, control and applications

MS Xavier, CD Tawk, A Zolfagharian, J Pinskier… - IEEE …, 2022 - ieeexplore.ieee.org
Soft robotics is a rapidly evolving field where robots are fabricated using highly deformable
materials and usually follow a bioinspired design. Their high dexterity and safety make them …

Model-based control of soft robots: A survey of the state of the art and open challenges

C Della Santina, C Duriez, D Rus - IEEE Control Systems …, 2023 - ieeexplore.ieee.org
From a functional standpoint, classic robots are not at all similar to biological systems. If
compared with rigid robots, animals' bodies look overly redundant, imprecise, and weak …

Soft robots modeling: A structured overview

C Armanini, F Boyer, AT Mathew… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The robotics community has seen an exponential growth in the level of complexity of the
theoretical tools presented for the modeling of soft robotics devices. Different solutions have …

Underwater soft robotics: A review of bioinspiration in design, actuation, modeling, and control

SM Youssef, MA Soliman, MA Saleh, MA Mousa… - Micromachines, 2022 - mdpi.com
Nature and biological creatures are some of the main sources of inspiration for humans.
Engineers have aspired to emulate these natural systems. As rigid systems become …

Learning neural constitutive laws from motion observations for generalizable pde dynamics

P Ma, PY Chen, B Deng… - International …, 2023 - proceedings.mlr.press
We propose a hybrid neural network (NN) and PDE approach for learning generalizable
PDE dynamics from motion observations. Many NN approaches learn an end-to-end model …

A survey of optimal transport for computer graphics and computer vision

N Bonneel, J Digne - Computer Graphics Forum, 2023 - Wiley Online Library
Optimal transport is a long‐standing theory that has been studied in depth from both
theoretical and numerical point of views. Starting from the 50s this theory has also found a …

Differentiable visual computing for inverse problems and machine learning

A Spielberg, F Zhong, K Rematas… - Nature Machine …, 2023 - nature.com
Modern 3D computer graphics technologies are able to reproduce the dynamics and
appearance of real-world environments and phenomena, building on theoretical models in …

Diffusebot: Breeding soft robots with physics-augmented generative diffusion models

THJ Wang, J Zheng, P Ma, Y Du… - Advances in …, 2023 - proceedings.neurips.cc
Nature evolves creatures with a high complexity of morphological and behavioral
intelligence, meanwhile computational methods lag in approaching that diversity and …

Differentiable simulation of soft multi-body systems

Y Qiao, J Liang, V Koltun, M Lin - Advances in Neural …, 2021 - proceedings.neurips.cc
We present a method for differentiable simulation of soft articulated bodies. Our work
enables the integration of differentiable physical dynamics into gradient-based pipelines …