Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Learning-based legged locomotion: State of the art and future perspectives
Legged locomotion holds the premise of universal mobility, a critical capability for many real-
world robotic applications. Both model-based and learning-based approaches have …
world robotic applications. Both model-based and learning-based approaches have …
Robot model identification and learning: A modern perspective
In recent years, the increasing complexity and safety-critical nature of robotic tasks have
highlighted the importance of accurate and reliable robot models. This trend has led to a …
highlighted the importance of accurate and reliable robot models. This trend has led to a …
Hood: Hierarchical graphs for generalized modelling of clothing dynamics
We propose a method that leverages graph neural networks, multi-level message passing,
and unsupervised training to enable real-time prediction of realistic clothing dynamics …
and unsupervised training to enable real-time prediction of realistic clothing dynamics …
NeuralSim: Augmenting differentiable simulators with neural networks
Differentiable simulators provide an avenue for closing the sim-to-real gap by enabling the
use of efficient, gradient-based optimization algorithms to find the simulation parameters that …
use of efficient, gradient-based optimization algorithms to find the simulation parameters that …
Fast and feature-complete differentiable physics for articulated rigid bodies with contact
We present a fast and feature-complete differentiable physics engine, Nimble
(nimblephysics. org), that supports Lagrangian dynamics and hard contact constraints for …
(nimblephysics. org), that supports Lagrangian dynamics and hard contact constraints for …
Learning neural constitutive laws from motion observations for generalizable pde dynamics
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 …
PDE dynamics from motion observations. Many NN approaches learn an end-to-end model …
Ppr: Physically plausible reconstruction from monocular videos
Given monocular videos, we build 3D models of articulated objects and environments
whose 3D configurations satisfy dynamics and contact constraints. At its core, our method …
whose 3D configurations satisfy dynamics and contact constraints. At its core, our method …
Accelerated policy learning with parallel differentiable simulation
Deep reinforcement learning can generate complex control policies, but requires large
amounts of training data to work effectively. Recent work has attempted to address this issue …
amounts of training data to work effectively. Recent work has attempted to address this issue …
Grasp'd: Differentiable contact-rich grasp synthesis for multi-fingered hands
The study of hand-object interaction requires generating viable grasp poses for high-
dimensional multi-finger models, often relying on analytic grasp synthesis which tends to …
dimensional multi-finger models, often relying on analytic grasp synthesis which tends to …
Pac-nerf: Physics augmented continuum neural radiance fields for geometry-agnostic system identification
Existing approaches to system identification (estimating the physical parameters of an
object) from videos assume known object geometries. This precludes their applicability in a …
object) from videos assume known object geometries. This precludes their applicability in a …