An overview of soft robotics
Soft robots' flexibility and compliance give them the potential to outperform traditional rigid-
bodied robots while performing multiple tasks in unexpectedly changing environments and …
bodied robots while performing multiple tasks in unexpectedly changing environments and …
Neural koopman pooling: Control-inspired temporal dynamics encoding for skeleton-based action recognition
Skeleton-based human action recognition is becoming increasingly important in a variety of
fields. Most existing works train a CNN or GCN based backbone to extract spatial-temporal …
fields. Most existing works train a CNN or GCN based backbone to extract spatial-temporal …
Koopman operators for modeling and control of soft robotics
Abstract Purpose of Review We review recent advances in algorithmic development and
validation for modeling and control of soft robots leveraging the Koopman operator theory …
validation for modeling and control of soft robots leveraging the Koopman operator theory …
Sim-to-real for soft robots using differentiable fem: Recipes for meshing, damping, and actuation
An accurate, physically-based, and differentiable model of soft robots can unlock
downstream applications in optimal control. The Finite Element Method (FEM) is an …
downstream applications in optimal control. The Finite Element Method (FEM) is an …
Multifactor sequential disentanglement via structured koopman autoencoders
Disentangling complex data to its latent factors of variation is a fundamental task in
representation learning. Existing work on sequential disentanglement mostly provides two …
representation learning. Existing work on sequential disentanglement mostly provides two …
Robust learning and control of time-delay nonlinear systems with deep recurrent Koopman operators
In this work, we consider the problem of Koopman modeling and data-driven predictive
control for a class of uncertain nonlinear systems subject to time delays. A robust deep …
control for a class of uncertain nonlinear systems subject to time delays. A robust deep …
Robust learning-based control for uncertain nonlinear systems with validation on a soft robot
Existing modeling and control methods for real-world systems typically deal with uncertainty
and nonlinearity on a case-by-case basis. We present a universal and robust control …
and nonlinearity on a case-by-case basis. We present a universal and robust control …
Generative modeling of regular and irregular time series data via koopman VAEs
Generating realistic time series data is important for many engineering and scientific
applications. Existing work tackles this problem using generative adversarial networks …
applications. Existing work tackles this problem using generative adversarial networks …
Extracting Koopman operators for prediction and control of non-linear dynamics using two-stage learning and oblique projections
D Uchida, K Duraisamy - arXiv preprint arXiv:2308.13051, 2023 - arxiv.org
The Koopman operator framework provides a perspective that non-linear dynamics can be
described through the lens of linear operators acting on function spaces. As the framework …
described through the lens of linear operators acting on function spaces. As the framework …
[HTML][HTML] Deep Koopman Operator-based degradation modelling
S Garmaev, O Fink - Reliability Engineering & System Safety, 2024 - Elsevier
Developing reliable health indicators for industrial assets is essential for accurate condition
monitoring, fault detection, and predicting the remaining useful lifetime. However …
monitoring, fault detection, and predicting the remaining useful lifetime. However …