4 papers · 1 filter
PhysCoRe: Physics-Corrected Residual World Models for Material-Aware Deformable Dynamics
Haocheng Yin, Shuohan Tao, Yongsheng Chen +1
Predicting how deformable objects evolve under robotic manipulation is a longstanding challenge. Existing approaches typically rely on per-object optimization to fit material param…
Beyond Topology: A Morphological Symmetry Graph Representation for Locomotion Policy Learning
Sizhe Wei, Xulin Chen, Fengze Xie +3
Reinforcement learning has enabled impressive locomotion skills on articulated robots, but common policy representations remain only weakly aligned with robot physics. Generic netw…
Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning
Fengze Xie, Sizhe Wei, Yue Song +2
We present a morphological-symmetry-equivariant heterogeneous graph neural network, namely MS-HGNN, for robotic dynamics learning, that integrates robotic kinematic structures and…
FetchBench: A Simulation Benchmark for Robot Fetching
Beining Han, Meenal Parakh, Derek Geng +3
Fetching, which includes approaching, grasping, and retrieving, is a critical challenge for robot manipulation tasks. Existing methods primarily focus on table-top scenarios, which…