From the 1 of 8 linked papers with an AI index.
6 papers · 1 filter
Scaling Behavior Foundation Model for Humanoid Robots
Weishuai Zeng, Kangning Yin, Xiaojie Niu +15
The paper proposes a scalable behavior foundation model for humanoid robots that uses a motion‑tracking learning paradigm, coordinated on‑policy rollouts and diverse reference moti…
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…
DyGRO-VLA: Cross-Task Scaling of Vision-Language-Action Models via Dynamic Grouped Residual Optimization
Sixu Lin, Yunpeng Qing, Litao Liu +4
Recent progress in Reinforcement Learning (RL) provides a principled approach to optimizing Vision-Language-Action (VLA) models, facilitating a shift from trajectory imitation to a…
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…
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…
Developing Path Planning with Behavioral Cloning and Proximal Policy Optimization for Path-Tracking and Static Obstacle Nudging
Mingyan Zhou, Biao Wang, Tian Tan +1
In autonomous driving, end-to-end methods utilizing Imitation Learning (IL) and Reinforcement Learning (RL) are becoming more and more common. However, they do not involve explicit…