7 papers
GaussianWAM: Distilling Geometry and Semantics from 3D Gaussian Fields into World-Action Models
Zijian Zhang, Yuqing Jiang, Weitao Zhou +6
World-Action Models (WAMs) jointly learn future visual prediction and action generation, using video dynamics as a representation-learning signal for robotic manipulation. However,…
Decision-Metric Alignment in Latent World Models: Diagnostics and Action-Conditioned Objectives for MPC Planning
Jiawei Wang, Ke Rui, Yushen Zuo +2
JEPA-style latent world models can use Euclidean distance to a goal latent as the cost for model-predictive control (MPC). Strong decoding of task variables, however, does not guar…
SoftVTBench: A Deformation-Aware Visuo-Tactile Dataset and Benchmark for Deformable-Object Manipulation
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Physical interaction quality is central to deformable-object manipulation, yet most benchmarks evaluate task success alone. A policy may complete the task while allowing slip or ca…
SoftVTBench: A Safety-Aware Visuo-Tactile Benchmark for Physically Constrained Robotic Manipulation of Deformable Objects (Early Version)
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Deformable object manipulation poses challenges beyond task completion: successful execution must also maintain safe physical interaction, holding the object stably without slip or…
HiFi-UMI: Learning Deployable Manipulation Policies from High-Fidelity UMI Data Alone
Simple AI, :, Yuteng Wei +16
Learning deployable manipulation policies is bottlenecked by the scarcity of data that is both high-fidelity and scalable. Real-robot teleoperation is accurate but costly to scale;…
EgoRecovery: Acquiring Failure Recovery Ability Through Human Recovery Demonstration
Zuhao Ge, Yuchen Zhou, Weitao Zhou +8
Robust embodied robots should be able to recover from failures and retry tasks in order to operate reliably in unstructured and noisy real-world environments. Achieving this capabi…