1 citations · 1 across the 11 of their papers we have counts for
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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…
A Safety-Critical Framework for UGVs in Complex Environments: A Data-Driven Discrepancy-Aware Approach
Skylar X. Wei, Lu Gan, Joel W. Burdick
This work presents a novel data-driven multi-layered planning and control framework for the safe navigation of a class of unmanned ground vehicles (UGVs) in the presence of unknown…