paper-with-me

Papers

A Unified and General Humanoid Whole-Body Controller for Versatile Locomotion

2025-02-05 · Yufei Xue, Wentao Dong, Minghuan Liu, Weinan Zhang, Jiangmiao Pang

Locomotion is a fundamental skill for humanoid robots. However, most existing works make locomotion a single, tedious, unextendable, and unconstrained movement. This limits the kinematic capabilities of humanoid robots. In contrast, humans possess versatile athletic abilities-running, jumping, hopping, and finely adjusting gait parameters such as frequency and foot height. In this paper, we investigate solutions to bring such versatility into humanoid locomotion and thereby propose HugWBC: a unified and general humanoid whole-body controller for versatile locomotion. By designing a general command space in the aspect of tasks and behaviors, along with advanced techniques like symmetrical loss and intervention training for learning a whole-body humanoid controlling policy in simulation, HugWBC enables real-world humanoid robots to produce various natural gaits, including walking, jumping, standing, and hopping, with customizable parameters such as frequency, foot swing height, further combined with different body height, waist rotation, and body pitch. Beyond locomotion, HugWBC also supports real-time interventions from external upper-body controllers like teleoperation, enabling loco-manipulation with precision under any locomotive behavior. Extensive experiments validate the high tracking accuracy and robustness of HugWBC with/without upper-body intervention for all commands, and we further provide an in-depth analysis of how the various commands affect humanoid movement and offer insights into the relationships between these commands. To our knowledge, HugWBC is the first humanoid whole-body controller that supports such versatile locomotion behaviors with high robustness and flexibility.

📄 PDF Abstract BibTeX arXiv:2502.03206

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

TWIST: Teleoperated Whole-Body Imitation System

2025-05-05 · Yanjie Ze, Zixuan Chen, João Pedro Araújo, Zi-ang Cao 외

Teleoperating humanoid robots in a whole-body manner marks a fundamental step toward developing general-purpose robotic intelligence, with human motion providing an ideal interface for controlling all degrees of freedom.…

Embodiment-Aware Generalist Specialist Distillation for Unified Humanoid Whole-Body Control

2026-02-03 · Quanquan Peng, Yunfeng Lin, Yufei Xue, Jiangmiao Pang 외 arxiv

Humanoid Whole-Body Controllers trained with reinforcement learning (RL) have recently achieved remarkable performance, yet many target a single robot embodiment. Variations in dynamics, degrees of freedom (DoFs), and ki…

Reinforcement Learning

ULTRA: Unified Multimodal Control for Autonomous Humanoid Whole-Body Loco-Manipulation

2026-03-03 · Xialin He, Sirui Xu, Xinyao Li, Runpei Dong 외 arxiv

Achieving autonomous and versatile whole-body loco-manipulation remains a central barrier to making humanoids practically useful. Yet existing approaches are fundamentally constrained: retargeted data are often scarce or…

Reinforcement Learning

KungfuBot2: Learning Versatile Motion Skills for Humanoid Whole-Body Control

2025-09-20 · Jinrui Han, Weiji Xie, Jiakun Zheng, Jiyuan Shi 외 arxiv

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 single policy must master a broad reper…

ULC: A Unified and Fine-Grained Controller for Humanoid Loco-Manipulation

2025-07-09 · Wandong Sun, Luying Feng, Baoshi Cao, Yang Liu 외 arxiv

Loco-Manipulation for humanoid robots aims to enable robots to integrate mobility with upper-body tracking capabilities. Most existing approaches adopt hierarchical architectures that decompose control into isolated uppe…