1 citations · 1 across the 26 of their papers we have counts for
12 papers · 1 filter
Towards Adaptive Humanoid Control via Multi-Behavior Distillation and Reinforced Fine-Tuning
Yingnan Zhao, Xinmiao Wang, Dewei Wang +5
Humanoid robots are promising to learn a diverse set of human-like locomotion behaviors, including standing up, walking, running, and jumping. However, existing methods predominant…
Towards Reliable LLM-based Robot Planning via Combined Uncertainty Estimation
Shiyuan Yin, Chenjia Bai, Zihao Zhang +4
Large language models (LLMs) demonstrate advanced reasoning abilities, enabling robots to understand natural language instructions and generate high-level plans with appropriate gr…
KungfuBot2: Learning Versatile Motion Skills for Humanoid Whole-Body Control
Jinrui Han, Weiji Xie, Jiakun Zheng +4
Learning versatile whole-body skills by tracking various human motions is a fundamental step toward general-purpose humanoid robots. This task is particularly challenging because a…
HumanoidGen: Data Generation for Bimanual Dexterous Manipulation via LLM Reasoning
Zhi Jing, Siyuan Yang, Jicong Ao +3
For robotic manipulation, existing robotics datasets and simulation benchmarks predominantly cater to robot-arm platforms. However, for humanoid robots equipped with dual arms and…
MoRE: Mixture of Residual Experts for Humanoid Lifelike Gaits Learning on Complex Terrains
Dewei Wang, Xinmiao Wang, Xinzhe Liu +4
Humanoid robots have demonstrated robust locomotion capabilities using Reinforcement Learning (RL)-based approaches. Further, to obtain human-like behaviors, existing methods integ…
Skill-Nav: Enhanced Navigation with Versatile Quadrupedal Locomotion via Waypoint Interface
Dewei Wang, Chenjia Bai, Chenhui Li +4
Quadrupedal robots have demonstrated exceptional locomotion capabilities through Reinforcement Learning (RL), including extreme parkour maneuvers. However, integrating locomotion s…
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…
Towards a Generalizable Bimanual Foundation Policy via Flow-based Video Prediction
Chenyou Fan, Fangzheng Yan, Chenjia Bai +4
Learning a generalizable bimanual manipulation policy is extremely challenging for embodied agents due to the large action space and the need for coordinated arm movements. Existin…
Adversarial Locomotion and Motion Imitation for Humanoid Policy Learning
Jiyuan Shi, Xinzhe Liu, Dewei Wang +6
Humans exhibit diverse and expressive whole-body movements. However, attaining human-like whole-body coordination in humanoid robots remains challenging, as conventional approaches…
Information-Theoretic Reward Decomposition for Generalizable RLHF
Liyuan Mao, Haoran Xu, Amy Zhang +2
A generalizable reward model is crucial in Reinforcement Learning from Human Feedback (RLHF) as it enables correctly evaluating unseen prompt-response pairs. However, existing rewa…
Humanoid Whole-Body Locomotion on Narrow Terrain via Dynamic Balance and Reinforcement Learning
Weiji Xie, Chenjia Bai, Jiyuan Shi +4
Humans possess delicate dynamic balance mechanisms that enable them to maintain stability across diverse terrains and under extreme conditions. However, despite significant advance…
Online Preference Alignment for Language Models via Count-based Exploration
Chenjia Bai, Yang Zhang, Shuang Qiu +3
Reinforcement Learning from Human Feedback (RLHF) has shown great potential in fine-tuning Large Language Models (LLMs) to align with human preferences. Existing methods perform pr…