7 citations · 22 across the 30 of their papers we have counts for
30 papers
AM-Bench: A Modular Simulation Suite and Benchmark for Aerial Manipulation Policy Learning
Yutong Wang, Dongjae Lee, Xiaofeng Guo +9
Standardized benchmarks have played a central role in advancing robot manipulation learning, yet most focus on ground-supported manipulation systems, which limits their applicabili…
Opening the Sim-to-Real Door for Humanoid Pixel-to-Action Policy Transfer
Haoru Xue, Tairan He, Zi Wang +9
Recent progress in GPU-accelerated, photorealistic simulation has opened a scalable data-generation path for robot learning, where massive physics and visual randomization allow po…
VIRAL: Visual Sim-to-Real at Scale for Humanoid Loco-Manipulation
Tairan He, Zi Wang, Haoru Xue +11
A key barrier to the real-world deployment of humanoid robots is the lack of autonomous loco-manipulation skills. We introduce VIRAL, a visual sim-to-real framework that learns hum…
BFM-Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning
Yitang Li, Zhengyi Luo, Tonghe Zhang +10
Building Behavioral Foundation Models (BFMs) for humanoid robots has the potential to unify diverse control tasks under a single, promptable generalist policy. However, existing ap…
Self-Improving Vision-Language-Action Models with Data Generation via Residual RL
Wenli Xiao, Haotian Lin, Andy Peng +9
Supervised fine-tuning (SFT) has become the de facto post-training strategy for large vision-language-action (VLA) models, but its reliance on costly human demonstrations limits sc…
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…
LeVERB: Humanoid Whole-Body Control with Latent Vision-Language Instruction
Haoru Xue, Xiaoyu Huang, Dantong Niu +8
Vision-language-action (VLA) models have demonstrated strong semantic understanding and zero-shot generalization, yet most existing systems assume an accurate low-level controller…
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,…
FALCON: Learning Force-Adaptive Humanoid Loco-Manipulation
Yuanhang Zhang, Yifu Yuan, Prajwal Gurunath +7
Humanoid loco-manipulation holds transformative potential for daily service and industrial tasks, yet achieving precise, robust whole-body control with 3D end-effector force intera…
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…
RAMBO: RL-Augmented Model-Based Whole-Body Control for Loco-Manipulation
Jin Cheng, Dongho Kang, Gabriele Fadini +2
Loco-manipulation, physical interaction of various objects that is concurrently coordinated with locomotion, remains a major challenge for legged robots due to the need for both pr…
Humanoid Policy ~ Human Policy
Ri-Zhao Qiu, Shiqi Yang, Xuxin Cheng +12
Training manipulation policies for humanoid robots with diverse data enhances their robustness and generalization across tasks and platforms. However, learning solely from robot de…
Whole-Body Model-Predictive Control of Legged Robots with MuJoCo
John Z. Zhang, Taylor A. Howell, Zeji Yi +6
We demonstrate the surprising real-world effectiveness of a very simple approach to whole-body model-predictive control (MPC) of quadruped and humanoid robots: the iterative LQR (i…
Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics
Yichao Zhong, Chong Zhang, Tairan He +1
Real-world legged locomotion systems often need to reconcile agility and safety for different scenarios. Moreover, the underlying dynamics are often unknown and time-variant (e.g.,…
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…
Humanoid Locomotion and Manipulation: Current Progress and Challenges in Control, Planning, and Learning
Zhaoyuan Gu, Junheng Li, Wenlan Shen +15
Humanoid robots hold great potential to perform various human-level skills, involving unified locomotion and manipulation in real-world settings. Driven by advances in machine lear…
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…
HOVER: Versatile Neural Whole-Body Controller for Humanoid Robots
Tairan He, Wenli Xiao, Toru Lin +9
Humanoid whole-body control requires adapting to diverse tasks such as navigation, loco-manipulation, and tabletop manipulation, each demanding a different mode of control. For exa…
Agile Mobility with Rapid Online Adaptation via Meta-learning and Uncertainty-aware MPPI
Dvij Kalaria, Haoru Xue, Wenli Xiao +3
Modern non-linear model-based controllers require an accurate physics model and model parameters to be able to control mobile robots at their limits. Also, due to surface slipping…
AnyCar to Anywhere: Learning Universal Dynamics Model for Agile and Adaptive Mobility
Wenli Xiao, Haoru Xue, Tony Tao +3
Recent works in the robot learning community have successfully introduced generalist models capable of controlling various robot embodiments across a wide range of tasks, such as n…
Full-Order Sampling-Based MPC for Torque-Level Locomotion Control via Diffusion-Style Annealing
Haoru Xue, Chaoyi Pan, Zeji Yi +2
Due to high dimensionality and non-convexity, real-time optimal control using full-order dynamics models for legged robots is challenging. Therefore, Nonlinear Model Predictive Con…
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…
Model-Based Diffusion for Trajectory Optimization
Chaoyi Pan, Zeji Yi, Guanya Shi +1
Recent advances in diffusion models have demonstrated their strong capabilities in generating high-fidelity samples from complex distributions through an iterative refinement proce…
OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning
Tairan He, Zhengyi Luo, Xialin He +6
We present OmniH2O (Omni Human-to-Humanoid), a learning-based system for whole-body humanoid teleoperation and autonomy. Using kinematic pose as a universal control interface, Omni…