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Found 9 papers, 2 papers with code
Fast Point Cloud to Mesh Reconstruction for Deformable Object Tracking
For a robotic hand to control soft objects, it has to acquire online state feedback of the deforming object.
A Structured Matrix Method for Nonequispaced Neural Operators
The computational efficiency of many neural operators, widely used for learning solutions of PDEs, relies on the fast Fourier transform (FFT) for performing spectral computations.
Autonomous Marker-less Rapid Aerial Grasping
In real-world experiments on a dynamically grasping aerial platform, we show that our system can replicate the performance of a motion capture system for object localization up to 94. 5 % of the baseline grasping success rate.
Meta-Learning via Classifier(-free) Diffusion Guidance
Our methods repurpose the popular generative image synthesis techniques of natural language guidance and diffusion models to generate neural network weights adapted for tasks.
Fast Aquatic Swimmer Optimization with Differentiable Projective Dynamics and Neural Network Hydrodynamic Models
For the deformable solid simulation of the swimmer's body, we use state-of-the-art techniques from the field of computer graphics to speed up the finite-element method (FEM).
Physics-constrained Unsupervised Learning of Partial Differential Equations using Meshes
Enhancing neural networks with knowledge of physical equations has become an efficient way of solving various physics problems, from fluid flow to electromagnetism.
Sim2Real for Soft Robotic Fish via Differentiable Simulation
Accurate simulation of soft mechanisms under dynamic actuation is critical for the design of soft robots.
DeSKO: Stability-Assured Robust Control with a Deep Stochastic Koopman Operator
Koopman operator theory linearly describes nonlinear dynamical systems in high-dimensional functional space, this facilitates the application of linear control methods to nonlinear systems.
DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation
The computational design of soft underwater swimmers is challenging because of the high degrees of freedom in soft-body modeling.
