8 papers
Systematically Exploring the Capabilities of GPT-6 Astra as Embodied Policies
Galbot Team, Xuchuan Chen, Xiaoqian Cheng +31
GPT-6 Astra exhibits a remarkable ability to generate numerical robot actions, extending its role beyond high-level planning. To assess Astra's capabilities as general-purpose embo…
Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking
Zekun Qi, Xuchuan Chen, Dairu Liu +10
We introduce Humanoid-GPT, a GPT-style Transformer with causal attention trained on a billion-scale motion corpus for whole-body control. Unlike prior shallow MLP trackers constrai…
Learning Athletic Humanoid Tennis Skills from Imperfect Human Motion Data
Zhikai Zhang, Haofei Lu, Yunrui Lian +12
Human athletes demonstrate versatile and highly-dynamic tennis skills to successfully conduct competitive rallies with a high-speed tennis ball. However, reproducing such behaviors…
Collision-Free Humanoid Traversal in Cluttered Indoor Scenes
Han Xue, Sikai Liang, Zhikai Zhang +7
We study the problem of collision-free humanoid traversal in cluttered indoor scenes, such as hurdling over objects scattered on the floor, crouching under low-hanging obstacles, o…
Track Any Motions under Any Disturbances
Zhikai Zhang, Jun Guo, Chao Chen +10
A foundational humanoid motion tracker is expected to be able to track diverse, highly dynamic, and contact-rich motions. More importantly, it needs to operate stably in real-world…
Unleashing Humanoid Reaching Potential via Real-world-Ready Skill Space
Zhikai Zhang, Chao Chen, Han Xue +6
Humans possess a large reachable space in the 3D world, enabling interaction with objects at varying heights and distances. However, realizing such large-space reaching on humanoid…
FreeMotion: MoCap-Free Human Motion Synthesis with Multimodal Large Language Models
Zhikai Zhang, Yitang Li, Haofeng Huang +2
Human motion synthesis is a fundamental task in computer animation. Despite recent progress in this field utilizing deep learning and motion capture data, existing methods are alwa…
How Can Everyday Users Efficiently Teach Robots by Demonstrations?
Maram Sakr, Zhikai Zhang, Benjamin Li +4
Learning from Demonstration (LfD) is a framework that allows lay users to easily program robots. However, the efficiency of robot learning and the robot's ability to generalize to…