11 papers
Towards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Tracking
Tao Huang, Ruofei Liu, Xuchen Tang +15
Humanoid robots have recently demonstrated promising capabilities in real-world ball sports. However, achieving professional motion styles while maintaining strong task performance…
CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning
Yuxin Chen, Hari Srikanth, Nathan Jew +7
While robot foundation models are growing increasingly capable, the strongest models are typically trained on proprietary data and remain closed-source, limiting downstream users'…
SMASH: Mastering Scalable Whole-Body Skills for Humanoid Ping-Pong with Egocentric Vision
Junli Ren, Yinghui Li, Kai Zhang +12
Existing humanoid table tennis systems remain limited by their reliance on external sensing and their inability to achieve agile whole-body coordination for precise task execution.…
Towards Adaptable Humanoid Control via Adaptive Motion Tracking
Tao Huang, Huayi Wang, Junli Ren +8
Humanoid robots are envisioned to adapt demonstrated motions to diverse real-world conditions while accurately preserving motion patterns. Existing motion prior approaches enable w…
PhysHSI: Towards a Real-World Generalizable and Natural Humanoid-Scene Interaction System
Huayi Wang, Wentao Zhang, Runyi Yu +10
Deploying humanoid robots to interact with real-world environments--such as carrying objects or sitting on chairs--requires generalizable, lifelike motions and robust scene percept…
Humanoid Goalkeeper: Learning from Position Conditioned Task-Motion Constraints
Junli Ren, Junfeng Long, Tao Huang +7
We present a reinforcement learning framework for autonomous goalkeeping with humanoid robots in real-world scenarios. While prior work has demonstrated similar capabilities on qua…
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…
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…
Learning Humanoid Locomotion with Perceptive Internal Model
Junfeng Long, Junli Ren, Moji Shi +4
In contrast to quadruped robots that can navigate diverse terrains using a "blind" policy, humanoid robots require accurate perception for stable locomotion due to their high degre…
FishMOT: A Simple and Effective Method for Fish Tracking Based on IoU Matching
Shuo Liu, Lulu Han, Xiaoyang Liu +4
Fish tracking plays a vital role in understanding fish behavior and ecology. However, existing tracking methods face challenges in accuracy and robustness dues to morphological cha…