7 papers · 1 filter
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…
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…