paper-with-me

Papers

PhysiFlow: Physics-Aware Humanoid Whole-Body VLA via Multi-Brain Latent Flow Matching and Robust Tracking

2026-03-05 · Weikai Qin, Sichen Wu, Ci Chen, Mengfan Liu, Linxi Feng, Xinru Cui, Haoqi Han, Hesheng Wang arxiv

In the domain of humanoid robot control, the fusion of Vision-Language-Action (VLA) with whole-body control is essential for semantically guided execution of real-world tasks. However, existing methods encounter challenges in terms of low VLA inference efficiency or an absence of effective semantic guidance for whole-body control, resulting in instability in dynamic limb-coordinated tasks. To bridge this gap, we present a semantic-motion intent guided, physics-aware multi-brain VLA framework for humanoid whole-body control. A series of experiments was conducted to evaluate the performance of the proposed framework. The experimental results demonstrated that the framework enabled reliable vision-language-guided full-body coordination for humanoid robots.

📄 PDF Abstract BibTeX arXiv:2603.05410

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

HUSKY: Humanoid Skateboarding System via Physics-Aware Whole-Body Control

2026-02-03 · Jinrui Han, Dewei Wang, Chenyun Zhang, Xinzhe Liu 외 arxiv

While current humanoid whole-body control frameworks predominantly rely on the static environment assumptions, addressing tasks characterized by high dynamism and complex interactions presents a formidable challenge. In …

ZeroWBC: Learning Natural Whole-Body Humanoid Interaction from Human Egocentric Data

2026-03-10 · Haoran Yang, Jiacheng Bao, Yucheng Xin, Haoming Song 외 arxiv

Achieving versatile and natural whole-body humanoid interaction control remains challenging due to the high cost of whole-body teleoperation data. We present ZeroWBC, a teleoperation-free framework that learns humanoid w…

Learning Whole-Body Humanoid Locomotion via Motion Generation and Motion Tracking

2026-04-19 · Zewei Zhang, Kehan Wen, Michael Xu, Junzhe He 외 arxiv

Whole-body humanoid locomotion is challenging due to high-dimensional control, morphological instability, and the need for real-time adaptation to various terrains using onboard perception. Directly applying reinforcemen…

Reinforcement Learning

ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills

2025-02-03 · Tairan He, Jiawei Gao, Wenli Xiao, Yuanhang Zhang 외

Humanoid robots hold the potential for unparalleled versatility in performing human-like, whole-body skills. However, achieving agile and coordinated whole-body motions remains a significant challenge due to the dynamics…

ThorArena: Benchmarking Humanoid Physical Interaction with Human Motion-Force Demonstrations

2026-07-07 · Chenhao Yu, Hongwu Wang, Weitao Zhang, Youhao Hu 외 arxiv

Humanoid robots are increasingly expected to perform contact-rich tasks that require not only accurate whole-body motion but also robust physical interaction with surrounding objects and humans. Although recent advances …