2 citations · 6 across the 13 of their papers we have counts for
14 papers
Towards High-DoF Dexterous Manipulation through VLA Post-Training
Junlei Zhu, Shenzhe Yao, Chaogui Huang +6
Imitation-learned vision--language--action (VLA) foundation models acquire broad manipulation capabilities by scaling robot data across tasks and embodiments, but reliable deployme…
MINT: A Unified Model for World-Space Camera and Hand Motion Estimation from Scalable Egocentric Pipeline Supervision
Zijie Zhu, Weiren Cai, Yizhou Wang +4
Recovering camera and hand motion in world coordinates from egocentric video is a key capability for activity understanding, robot learning, and augmented reality. Existing systems…
OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining
Yuran Wang, Siqiao Huang, Mingleyang Li +21
World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are…
LD4WAM: Learning Latent Dynamics from Human Videos for World Action Models
Zhenhao Shen, Jiaqi Liang, Jasper Lu +11
Human video is playing an increasingly central role in training World Action Models (WAMs), owing to its diversity and low collection cost relative to teleoperated robot data. Howe…
TopoRetarget: Interaction-Preserving Retargeting for Dexterous Manipulation
Jielin Wu, Shenzhe Yao, Guanqi He +6
Human hand-object demonstrations provide dense reference motions for training dexterous manipulation reinforcement learning (RL) policies through reference tracking. However, to us…
OMG: Omni-Modal Motion Generation for Generalist Humanoid Control
Siqiao Huang, Kun-Ying Lee, Dongming Qiao +5
Humanoid whole-body control has made significant progress in recent years, yet existing approaches remain limited to few-skill policies with heavy reward engineering, or motion tra…
Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control
Yitang Li, Yuanhang Zhang, Wenli Xiao +5
Can your humanoid walk up and hand you a full cup of beer, without spilling a drop? While humanoids are increasingly featured in flashy demos like dancing, delivering packages, tra…
Sampling-Based System Identification with Active Exploration for Legged Robot Sim2Real Learning
Nikhil Sobanbabu, Guanqi He, Tairan He +2
Sim-to-real discrepancies hinder learning-based policies from achieving high-precision tasks in the real world. While Domain Randomization (DR) is commonly used to bridge this gap,…
Flying Hand: End-Effector-Centric Framework for Versatile Aerial Manipulation Teleoperation and Policy Learning
Guanqi He, Xiaofeng Guo, Luyi Tang +6
Aerial manipulation has recently attracted increasing interest from both industry and academia. Previous approaches have demonstrated success in various specific tasks. However, th…
ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills
Tairan He, Jiawei Gao, Wenli Xiao +15
Humanoid robots hold the potential for unparalleled versatility in performing human-like, whole-body skills. However, achieving agile and coordinated whole-body motions remains a s…
Self-Supervised Meta-Learning for All-Layer DNN-Based Adaptive Control with Stability Guarantees
Guanqi He, Yogita Choudhary, Guanya Shi
A critical goal of adaptive control is enabling robots to rapidly adapt in dynamic environments. Recent studies have developed a meta-learning-based adaptive control scheme, which…
Flying Calligrapher: Contact-Aware Motion and Force Planning and Control for Aerial Manipulation
Xiaofeng Guo, Guanqi He, Jiahe Xu +4
Aerial manipulation has gained interest in completing high-altitude tasks that are challenging for human workers, such as contact inspection and defect detection, etc. Previous res…
CoVO-MPC: Theoretical Analysis of Sampling-based MPC and Optimal Covariance Design
Zeji Yi, Chaoyi Pan, Guanqi He +2
Sampling-based Model Predictive Control (MPC) has been a practical and effective approach in many domains, notably model-based reinforcement learning, thanks to its flexibility and…
Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion
Tairan He, Chong Zhang, Wenli Xiao +3
Legged robots navigating cluttered environments must be jointly agile for efficient task execution and safe to avoid collisions with obstacles or humans. Existing studies either de…