18 citations · 18 across the 4 of their papers we have counts for
5 papers
FluxVLA Engine: A One-Stop VLA Engineering Platform for Embodied Intelligence
Yinhao Li, Weixin Mao, Zihan Lan +22
Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of embodied policies, yet turning…
CWI: Composite Humanoid Whole-Body Imitation System for Loco-manipulation
Wenqi Ge, Junde Guo, Zhen Fu +3
Achieving everyday tasks with humanoid robots requires coordinating stable locomotion with versatile manipulation. However, existing whole-body controllers still face significant c…
Beyond Pixels: Learning Invariant Rewards for Real-World Robotics From a Few Demonstrations
Tengye Xu, Yangting Sun, Ziju Shen +5
Designing reward functions that generalize beyond controlled laboratory settings remains a fundamental challenge in reinforcement learning for robotics. In open-world manipulation…
Multi-Loco: Unifying Multi-Embodiment Legged Locomotion via Reinforcement Learning Augmented Diffusion
Shunpeng Yang, Zhen Fu, Zhefeng Cao +4
Generalizing locomotion policies across diverse legged robots with varying morphologies is a key challenge due to differences in observation/action dimensions and system dynamics.…
Learning Whole-Body Loco-Manipulation for Omni-Directional Task Space Pose Tracking with a Wheeled-Quadrupedal-Manipulator
Kaiwen Jiang, Zhen Fu, Junde Guo +2
In this paper, we study the whole-body loco-manipulation problem using reinforcement learning (RL). Specifically, we focus on the problem of how to coordinate the floating base and…