3 citations · 4 across the 7 of their papers we have counts for
8 papers
Worlds in One Demo: A Synthetic Data Engine for Learning Open-World Mobile Manipulation
Lingxiao Guo, Huanyu Li, Guanya Shi
Learning open-world mobile manipulation policies requires vast data to achieve spatial generalization, long-horizon robustness, and scene generalization. Current prevailing data co…
PCHC: Enabling Preference Conditioned Humanoid Control via Multi-Objective Reinforcement Learning
Huanyu Li, Dewei Wang, Xinmiao Wang +4
Humanoid robots often need to balance competing objectives, such as maximizing speed while minimizing energy consumption. While current reinforcement learning (RL) methods can mast…
Failure-Aware RL: Reliable Offline-to-Online Reinforcement Learning with Self-Recovery for Real-World Manipulation
Huanyu Li, Kun Lei, Sheng Zang +5
Post-training algorithms based on deep reinforcement learning can push the limits of robotic models for specific objectives, such as generalizability, accuracy, and robustness. How…
LLM-Cave: A benchmark and light environment for large language models reasoning and decision-making system
Huanyu Li, Zongyuan Li, Wei Huang +1
Large language models (LLMs) such as ChatGPT o1, ChatGPT o3, and DeepSeek R1 have shown great potential in solving difficult problems. However, current LLM evaluation benchmarks ar…
RL-100: Performant Robotic Manipulation with Real-World Reinforcement Learning
Kun Lei, Huanyu Li, Dongjie Yu +6
Real-world robotic manipulation in homes and factories demands reliability, efficiency, and robustness that approach or surpass those of skilled human operators. We present RL-100,…
KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills
Weiji Xie, Jinrui Han, Jiakun Zheng +6
Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of tracking smooth, low-speed human motions, eve…
Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets
Guangqi Jiang, Yifei Sun, Tao Huang +3
The pre-training of visual representations has enhanced the efficiency of robot learning. Due to the lack of large-scale in-domain robotic datasets, prior works utilize in-the-wild…
UniFolding: Towards Sample-efficient, Scalable, and Generalizable Robotic Garment Folding
Han Xue, Yutong Li, Wenqiang Xu +3
This paper explores the development of UniFolding, a sample-efficient, scalable, and generalizable robotic system for unfolding and folding various garments. UniFolding employs the…