17 citations · 24 across the 18 of their papers we have counts for
19 papers · 1 filter
Workhorse: Learning Robust Whole-Body Humanoid Loco-Manipulation from Human Data
Songbo Hu, Qiayuan Liao, Yufeng Chi +4
Humanoid robots still struggle to plan contact-rich whole-body manipulation from egocentric RGB and proprioception. Workhorse learns such manipulation from robot-free human demonst…
SPARK: Skeleton-Parameter Aligned Retargeting on Humanoid Robots with Kinodynamic Trajectory Optimization
Hanwen Wang, Qiayuan Liao, Bike Zhang +3
Human motion provides rich priors for training general-purpose humanoid control policies, but raw demonstrations are often incompatible with a robot's kinematics and dynamics, limi…
mjlab: A Lightweight Framework for GPU-Accelerated Robot Learning
Kevin Zakka, Qiayuan Liao, Brent Yi +3
We present mjlab, a lightweight, open-source framework for robot learning that combines GPU-accelerated simulation with composable environments and minimal setup friction. mjlab ad…
HITTER: A HumanoId Table TEnnis Robot via Hierarchical Planning and Learning
Zhi Su, Bike Zhang, Nima Rahmanian +5
Humanoid robots have recently achieved impressive progress in locomotion and whole-body control, yet they remain constrained in tasks that demand rapid interaction with dynamic env…
BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion
Qiayuan Liao, Takara E. Truong, Xiaoyu Huang +4
The human-like form of humanoid robots positions them uniquely to achieve the agility and versatility in motor skills that humans possess. Learning from human demonstrations offers…
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…
LangWBC: Language-directed Humanoid Whole-Body Control via End-to-end Learning
Yiyang Shao, Xiaoyu Huang, Bike Zhang +6
General-purpose humanoid robots are expected to interact intuitively with humans, enabling seamless integration into daily life. Natural language provides the most accessible mediu…
Demonstrating Berkeley Humanoid Lite: An Open-source, Accessible, and Customizable 3D-printed Humanoid Robot
Yufeng Chi, Qiayuan Liao, Junfeng Long +5
Despite significant interest and advancements in humanoid robotics, most existing commercially available hardware remains high-cost, closed-source, and non-transparent within the r…
RoboCopilot: Human-in-the-loop Interactive Imitation Learning for Robot Manipulation
Philipp Wu, Yide Shentu, Qiayuan Liao +5
Learning from human demonstration is an effective approach for learning complex manipulation skills. However, existing approaches heavily focus on learning from passive human demon…
MuJoCo Playground
Kevin Zakka, Baruch Tabanpour, Qiayuan Liao +10
We introduce MuJoCo Playground, a fully open-source framework for robot learning built with MJX, with the express goal of streamlining simulation, training, and sim-to-real transfe…
DDAT: Diffusion Policies Enforcing Dynamically Admissible Robot Trajectories
Jean-Baptiste Bouvier, Kanghyun Ryu, Kartik Nagpal +3
Diffusion models excel at creating images and videos thanks to their multimodal generative capabilities. These same capabilities have made diffusion models increasingly popular in…
Learning Smooth Humanoid Locomotion through Lipschitz-Constrained Policies
Zixuan Chen, Xialin He, Yen-Jen Wang +8
Reinforcement learning combined with sim-to-real transfer offers a general framework for developing locomotion controllers for legged robots. To facilitate successful deployment in…
CurricuLLM: Automatic Task Curricula Design for Learning Complex Robot Skills using Large Language Models
Kanghyun Ryu, Qiayuan Liao, Zhongyu Li +3
Curriculum learning is a training mechanism in reinforcement learning (RL) that facilitates the achievement of complex policies by progressively increasing the task difficulty duri…
Berkeley Humanoid: A Research Platform for Learning-based Control
Qiayuan Liao, Bike Zhang, Xuanyu Huang +3
We introduce Berkeley Humanoid, a reliable and low-cost mid-scale humanoid research platform for learning-based control. Our lightweight, in-house-built robot is designed specifica…
HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation
Xiaoyu Huang, Qiayuan Liao, Yiming Ni +5
This work presents HiLMa-Res, a hierarchical framework leveraging reinforcement learning to tackle manipulation tasks while performing continuous locomotion using quadrupedal robot…
Leveraging Symmetry in RL-based Legged Locomotion Control
Zhi Su, Xiaoyu Huang, Daniel Ordoñez-Apraez +8
Model-free reinforcement learning is a promising approach for autonomously solving challenging robotics control problems, but faces exploration difficulty without information of th…
Walking in Narrow Spaces: Safety-critical Locomotion Control for Quadrupedal Robots with Duality-based Optimization
Qiayuan Liao, Zhongyu Li, Akshay Thirugnanam +2
This paper presents a safety-critical locomotion control framework for quadrupedal robots. Our goal is to enable quadrupedal robots to safely navigate in cluttered environments. To…
Real-time Trajectory Optimization and Control for Ball Bumping with Quadruped Robots
Qiayuan Liao, Zhefeng Cao, Hua Chen +1
This paper studies real-time motion planning and control for ball bumping motion with quadruped robots. To enable the quadruped to bump the flying ball with different initializatio…
Review of Quadruped Robots for Dynamic Locomotion
Qiayuan Liao
This review introduces quadruped robots: MITCheetah, HyQ, ANYmal, BigDog, and their mechanical structure, actuation, and control.