6 papers · 1 filter
Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
Guanxiong Chen, Qianjun Xia, Jiawei Peng +21
Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover…
MemoryVAM: Integrating Memory into Video Action Model for Robot Manipulation
Yuxin Jiang, Chang Yu, Yunuo Chen +4
Video-world-model policies learn action-relevant representations by predicting future observations. However, they condition on only a short observation window, which renders long-h…
Sparse2Act: Learning Action-Aligned Sparse 3D Representations for Cross-Domain Robot Manipulation
Yu Guo, Chang Yu, Siyu Ma +4
Explicit 3D representations are attractive for manipulation because they expose object shape, workspace geometry, and robot-object relations in metric coordinates. However, sparse…
TacCoRL: Integrating Tactile Feedback into VLA via Simulation
Siyu Ma, Yuqi Liang, Chang Yu +5
Vision-language-action (VLA) models provide strong visual, language, and action priors for robot manipulation, but visual observations alone often miss the local contact state requ…
EMPM: Embodied MPM for Modeling and Simulation of Deformable Objects
Yunuo Chen, Yafei Hu, Lingfeng Sun +3
Modeling deformable objects - especially continuum materials - in a way that is physically plausible, generalizable, and data-efficient remains challenging across 3D vision, graphi…
GRIP: A General Robotic Incremental Potential Contact Simulation Dataset for Unified Deformable-Rigid Coupled Grasping
Siyu Ma, Wenxin Du, Chang Yu +7
Grasping is fundamental to robotic manipulation, and recent advances in large-scale grasping datasets have provided essential training data and evaluation benchmarks, accelerating…