7 papers · 1 filter
ForkCast: Predictive Recovery for Vision-Language-Action Policies via Counterfactual Futures
Chenru Wen, Huajian Zeng, Haokai Ding +5
Vision-language-action (VLA) policies perform manipulation tasks using camera images and language instructions, but object slip or visual occlusion can disrupt execution. Recovery…
The Robot Data Factory
Sami Haddadin, Ivan Laptev, Ian Reid +18
Physical AI requires more than increasingly large robot datasets: intelligent robots acquire knowledge through continuous interaction with the physical world. We argue that the def…
World-Action Models for Robot Learning and Control: A Survey
Zuxing Lu, Hongjia Zhai, Guanzhi Wang +13
Robots operating in open environments act under partial observability, physical constraints, and dynamic task contexts. Beyond mapping observations and language instructions to act…
MAC-I: Learned Metrics-Aware Covariance for Robust Visual-Inertial Fusion in Initialization and Calibration
Xiang Fei, Yuheng Qiu, Can Xu +5
Visual-Inertial (VI) fusion is fundamental to accurate and robust state estimation, where camera and IMU measurements are combined according to their respective uncertainties. Exis…
LooperMuscle: Fast and Stable Learning of Humanoid Whole-Body Tracking via Structured Mixture-of-Experts
Boyi Liu, Qijin Li, Tianqi Yu +2
FastSAC-style methods significantly reduce humanoid motion training time but often suffer from notable performance degradation compared with PPO in whole-body tracking tasks. We ta…
M3imic: Learning a Versatile Whole-Body Controller for Multimodal Motion Mimicking
Zuxing Lu, Ziang Zheng, Yao Lyu +7
Building a general-purpose whole-body controller is essential for enabling diverse motion capabilities in humanoid robots across a wide range of downstream tasks, including locomot…
VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis
Xiaolei Lang, Yang Wang, Yukun Zhou +10
Recent advances in robot foundation models trained on large-scale human teleoperation data have enabled robots to perform increasingly complex real-world tasks. However, scaling th…