7 citations · 22 across the 16 of their papers we have counts for
14 papers · 1 filter
GOTT: Object-centric Dexterous Manipulation with a Reusable Cross-Embodiment Primitive
Yulin Liu, Lai Wei, Yen-Jen Wang +4
Foundation models and large-scale human data provide rich sources of manipulation intent, but translating this intent into multi-fingered robot behavior remains difficult. Dexterou…
VLK: Learning Humanoid Loco-Manipulation from Synthetic Interactions in Reconstructed Scenes
Yen-Jen Wang, Jiaman Li, Sirui Chen +9
Perception-based humanoid loco-manipulation requires connecting egocentric observations and task instructions to whole-body motion. Learning this mapping requires synchronized egoc…
Coordinated Humanoid Manipulation with Choice Policies
Haozhi Qi, Yen-Jen Wang, Toru Lin +4
Humanoid robots hold great promise for operating in human-centric environments, yet achieving robust whole-body coordination across the head, hands, and legs remains a major challe…
Learning Dexterous Manipulation Skills from Imperfect Simulations
Elvis Hsieh, Wen-Han Hsieh, Yen-Jen Wang +4
Reinforcement learning and sim-to-real transfer have made significant progress in dexterous manipulation. However, progress remains limited by the difficulty of simulating complex…
HuB: Learning Extreme Humanoid Balance
Tong Zhang, Boyuan Zheng, Ruiqian Nai +8
The human body demonstrates exceptional motor capabilities-such as standing steadily on one foot or performing a high kick with the leg raised over 1.5 meters-both requiring precis…
RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning
Haoran Geng, Feishi Wang, Songlin Wei +34
Data scaling and standardized evaluation benchmarks have driven significant advances in natural language processing and computer vision. However, robotics faces unique challenges i…
Improving Vision-Language-Action Model with Online Reinforcement Learning
Yanjiang Guo, Jianke Zhang, Xiaoyu Chen +4
Recent studies have successfully integrated large vision-language models (VLMs) into low-level robotic control by supervised fine-tuning (SFT) with expert robotic datasets, resulti…
Prediction with Action: Visual Policy Learning via Joint Denoising Process
Yanjiang Guo, Yucheng Hu, Jianke Zhang +4
Diffusion models have demonstrated remarkable capabilities in image generation tasks, including image editing and video creation, representing a good understanding of the physical…
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…
Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning
Xinyang Gu, Yen-Jen Wang, Xiang Zhu +4
Humanoid robots, with their human-like skeletal structure, are especially suited for tasks in human-centric environments. However, this structure is accompanied by additional chall…
Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer
Xinyang Gu, Yen-Jen Wang, Jianyu Chen
Humanoid-Gym is an easy-to-use reinforcement learning (RL) framework based on Nvidia Isaac Gym, designed to train locomotion skills for humanoid robots, emphasizing zero-shot trans…
Prompt a Robot to Walk with Large Language Models
Yen-Jen Wang, Bike Zhang, Jianyu Chen +1
Large language models (LLMs) pre-trained on vast internet-scale data have showcased remarkable capabilities across diverse domains. Recently, there has been escalating interest in…
DoReMi: Grounding Language Model by Detecting and Recovering from Plan-Execution Misalignment
Yanjiang Guo, Yen-Jen Wang, Lihan Zha +1
Large language models (LLMs) encode a vast amount of semantic knowledge and possess remarkable understanding and reasoning capabilities. Previous work has explored how to ground LL…
Decentralized Motor Skill Learning for Complex Robotic Systems
Yanjiang Guo, Zheyuan Jiang, Yen-Jen Wang +2
Reinforcement learning (RL) has achieved remarkable success in complex robotic systems (eg. quadruped locomotion). In previous works, the RL-based controller was typically implemen…