3 citations · 6 across the 16 of their papers we have counts for
16 papers
GRAIL: Generating Humanoid Loco-Manipulation from World Models
Tianyi Xie, Haotian Zhang, Jinhyung Park +17
Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleoperation and motion capture a…
Feel Robot Feels: Tactile Feedback Array Glove for Dexterous Manipulation
Feiyu Jia, Xiaojie Niu, Sizhe Yang +5
Teleoperation is a key approach for collecting high-quality, physically consistent demonstrations for robotic manipulation. However, teleoperation for dexterous manipulation remain…
One-Policy-Fits-All: Geometry-Aware Action Latents for Cross-Embodiment Manipulation
Juncheng Mu, Sizhe Yang, Hojin Bae +5
Cross-embodiment manipulation is crucial for enhancing the scalability of robot manipulation and reducing the high cost of data collection. However, the significant differences bet…
Opening the Sim-to-Real Door for Humanoid Pixel-to-Action Policy Transfer
Haoru Xue, Tairan He, Zi Wang +9
Recent progress in GPU-accelerated, photorealistic simulation has opened a scalable data-generation path for robot learning, where massive physics and visual randomization allow po…
VIRAL: Visual Sim-to-Real at Scale for Humanoid Loco-Manipulation
Tairan He, Zi Wang, Haoru Xue +11
A key barrier to the real-world deployment of humanoid robots is the lack of autonomous loco-manipulation skills. We introduce VIRAL, a visual sim-to-real framework that learns hum…
Gallant: Voxel Grid-based Humanoid Locomotion and Local-navigation across 3D Constrained Terrains
Qingwei Ben, Botian Xu, Kailin Li +6
Robust humanoid locomotion requires accurate and globally consistent perception of the surrounding 3D environment. However, existing perception modules, mainly based on depth image…
SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control
Zhengyi Luo, Ye Yuan, Tingwu Wang +25
Despite the rise of billion-parameter foundation models trained across thousands of graphical processing units (GPUs), similar scaling gains have not been shown for humanoid contro…
SMAP: Self-supervised Motion Adaptation for Physically Plausible Humanoid Whole-body Control
Haoyu Zhao, Sixu Lin, Qingwei Ben +5
This paper presents a novel framework that enables real-world humanoid robots to maintain stability while performing human-like motion. Current methods train a policy which allows…
TeleOpBench: A Simulator-Centric Benchmark for Dual-Arm Dexterous Teleoperation
Hangyu Li, Qin Zhao, Haoran Xu +10
Teleoperation is a cornerstone of embodied-robot learning, and bimanual dexterous teleoperation in particular provides rich demonstrations that are difficult to obtain with fully a…
VB-Com: Learning Vision-Blind Composite Humanoid Locomotion Against Deficient Perception
Junli Ren, Tao Huang, Huayi Wang +6
The performance of legged locomotion is closely tied to the accuracy and comprehensiveness of state observations. Blind policies, which rely solely on proprioception, are considere…
HOMIE: Humanoid Loco-Manipulation with Isomorphic Exoskeleton Cockpit
Qingwei Ben, Feiyu Jia, Jia Zeng +3
Generalizable humanoid loco-manipulation poses significant challenges, requiring coordinated whole-body control and precise, contact-rich object manipulation. To address this, this…
BeamDojo: Learning Agile Humanoid Locomotion on Sparse Footholds
Huayi Wang, Zirui Wang, Junli Ren +4
Traversing risky terrains with sparse footholds poses a significant challenge for humanoid robots, requiring precise foot placements and stable locomotion. Existing learning-based…
Learning Humanoid Standing-up Control across Diverse Postures
Tao Huang, Junli Ren, Huayi Wang +6
Standing-up control is crucial for humanoid robots, with the potential for integration into current locomotion and loco-manipulation systems, such as fall recovery. Existing approa…
GRUtopia: Dream General Robots in a City at Scale
Hanqing Wang, Jiahe Chen, Wensi Huang +19
Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Rea…
DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation
Zilin Si, Gu Zhang, Qingwei Ben +4
We introduce DIFFTACTILE, a physics-based differentiable tactile simulation system designed to enhance robotic manipulation with dense and physically accurate tactile feedback. In…
RoboDuet: Learning a Cooperative Policy for Whole-body Legged Loco-Manipulation
Guoping Pan, Qingwei Ben, Zhecheng Yuan +6
Fully leveraging the loco-manipulation capabilities of a quadruped robot equipped with a robotic arm is non-trivial, as it requires controlling all degrees of freedom (DoFs) of the…