14 papers · 1 filter
RoboStriker: Latent-Space Strategic Games for Autonomous Humanoid Boxing
Kangning Yin, Kaige Liu, Zhe Cao +9
Achieving human-level competitive intelligence and physical agility in humanoid robots remains a profound challenge, particularly in contact-rich and highly dynamic tasks such as b…
Scaling Behavior Foundation Model for Humanoid Robots
Weishuai Zeng, Kangning Yin, Xiaojie Niu +15
Humanoid control requires natural whole-body coordination, precise real-time responses to control signals, and robust generalization across diverse environmental contexts, making i…
HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation
Shaopeng Zhai, Qi Zhang, Tianyi Zhang +5
When adapting Vision Language Action (VLA) models to downstream tasks, multiple rounds of post-training are often required to progressively address policy weaknesses. In this repor…
RoboSnap: One-Shot Real-to-Sim Scene Generation for Generalizable Robot Learning and Evaluation
Shujie Zhang, Jingkun Yi, Weipeng Zhong +6
Recovering real-world scenes as interactive simulation environments can enable generalizable robot learning and reproducible policy evaluation. However, constructing scenes that ar…
EBench: Elemental Diagnosis of Generalist Mobile Manipulation Policies
Ning Gao, Jinliang Zheng, Xing Gao +22
We present EBench, a simulation benchmark that diagnoses generalist mobile manipulation policies beyond a single success-rate scalar. EBench comprises 26 diverse and challenging ma…
Embodiment-Aware Generalist Specialist Distillation for Unified Humanoid Whole-Body Control
Quanquan Peng, Yunfeng Lin, Yufei Xue +2
Humanoid Whole-Body Controllers trained with reinforcement learning (RL) have recently achieved remarkable performance, yet many target a single robot embodiment. Variations in dyn…
Scalable and General Whole-Body Control for Cross-Humanoid Locomotion
Yufei Xue, YunFeng Lin, Wentao Dong +6
Learning-based whole-body controllers have become a key driver for humanoid robots, yet most existing approaches require robot-specific training. In this paper, we study the proble…
RoboStriker: Hierarchical Decision-Making for Autonomous Humanoid Boxing
Kangning Yin, Zhe Cao, Wentao Dong +7
Achieving human-level competitive intelligence and physical agility in humanoid robots remains a major challenge, particularly in contact-rich and highly dynamic tasks such as boxi…
UniCon: A Unified System for Efficient Robot Learning Transfers
Yunfeng Lin, Li Xu, Yong Yu +2
Deploying learning-based controllers across heterogeneous robots is challenging due to platform differences, inconsistent interfaces, and inefficient middleware. To address these i…
H-Zero: Cross-Humanoid Locomotion Pretraining Enables Few-shot Novel Embodiment Transfer
Yunfeng Lin, Minghuan Liu, Yufei Xue +4
The rapid advancement of humanoid robotics has intensified the need for robust and adaptable controllers to enable stable and efficient locomotion across diverse platforms. However…
UniTracker: Learning Universal Whole-Body Motion Tracker for Humanoid Robots
Kangning Yin, Weishuai Zeng, Ke Fan +7
Achieving expressive and generalizable whole-body motion control is essential for deploying humanoid robots in real-world environments. In this work, we propose UniTracker, a three…
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…
ReSim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation
Xiaoshen Han, Junqiu Yu, Minghuan Liu +6
Real-world data collection for robotics is costly and resource-intensive, requiring skilled operators and expensive hardware. Simulations offer a scalable alternative but often fai…
A Unified and General Humanoid Whole-Body Controller for Versatile Locomotion
Yufei Xue, Wentao Dong, Minghuan Liu +2
Locomotion is a fundamental skill for humanoid robots. However, most existing works make locomotion a single, tedious, unextendable, and unconstrained movement. This limits the kin…