Modeling and simulation of dynamics in soft robotics: A review of numerical approaches

L Qin, H Peng, X Huang, M Liu, W Huang - Current Robotics Reports, 2024 - Springer
Purpose of review In this review, we briefly summarize the numerical methods commonly
used for the nonlinear dynamic analysis of soft robotic systems. The underlying mechanical …

Recent progress on underwater soft robots: Adhesion, grabbing, actuating, and sensing

Y Zhang, D Kong, Y Shi, M Cai, Q Yu, S Li… - … in Bioengineering and …, 2023 - frontiersin.org
The research on biomimetic robots, especially soft robots with flexible materials as the main
structure, is constantly being explored. It integrates multi-disciplinary content, such as …

Segmenting mechanically heterogeneous domains via unsupervised learning

Q Nguyen, E Lejeune - Biomechanics and Modeling in Mechanobiology, 2024 - Springer
From biological organs to soft robotics, highly deformable materials are essential
components of natural and engineered systems. These highly deformable materials can …

[HTML][HTML] Gecko adhesion based sea star crawler robot

S Acharya, P Roberts, T Rane, R Singhal… - Frontiers in Robotics …, 2023 - frontiersin.org
Over the years, efforts in bioinspired soft robotics have led to mobile systems that emulate
features of natural animal locomotion. This includes combining mechanisms from multiple …

A Fabrication and Simulation Recipe for Untethering Soft-Rigid Robots with Cable-Driven Stiffness Modulation

JM Bern, ZJ Patterson, LZ Yañez… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
We explore the idea of robotic mechanisms that can shift between soft and rigid states, with
the long-term goal of creating robots that marry the flexibility and robustness of soft robots …

Inverse Design of Snap-Actuated Jumping Robots Powered by Mechanics-Aided Machine Learning

D Tong, Z Hao, M Liu, W Huang - arXiv preprint arXiv:2408.10470, 2024 - arxiv.org
Exploring the design and control strategies of soft robots through simulation is highly
attractive due to its cost-effectiveness. Although many existing models (eg, finite element …

Machine learning-driven gas identification in gas sensors

S Huang, A Croy, B Ibarlucea, G Cuniberti - Machine Learning for …, 2023 - Springer
Gas identification plays a critical role in characterizing our (chemical) environment. It allows
to warn of hazardous gases and may help to diagnose medical conditions. Miniaturized gas …