Zobrazeno 1 - 10
of 2 201
pro vyhledávání: '"Huang, Xiaoyu"'
We introduce Berkeley Humanoid, a reliable and low-cost mid-scale humanoid research platform for learning-based control. Our lightweight, in-house-built robot is designed specifically for learning algorithms with low simulation complexity, anthropomo
Externí odkaz:
http://arxiv.org/abs/2407.21781
Autor:
Huang, Xiaoyu, Liao, Qiayuan, Ni, Yiming, Li, Zhongyu, Smith, Laura, Levine, Sergey, Peng, Xue Bin, Sreenath, Koushil
This work presents HiLMa-Res, a hierarchical framework leveraging reinforcement learning to tackle manipulation tasks while performing continuous locomotion using quadrupedal robots. Unlike most previous efforts that focus on solving a specific task,
Externí odkaz:
http://arxiv.org/abs/2407.06584
Autor:
Huang, Xiaoyu, Chi, Yufeng, Wang, Ruofeng, Li, Zhongyu, Peng, Xue Bin, Shao, Sophia, Nikolic, Borivoje, Sreenath, Koushil
This work introduces DiffuseLoco, a framework for training multi-skill diffusion-based policies for dynamic legged locomotion from offline datasets, enabling real-time control of diverse skills on robots in the real world. Offline learning at scale h
Externí odkaz:
http://arxiv.org/abs/2404.19264
Autor:
Su, Zhi, Huang, Xiaoyu, Ordoñez-Apraez, Daniel, Li, Yunfei, Li, Zhongyu, Liao, Qiayuan, Turrisi, Giulio, Pontil, Massimiliano, Semini, Claudio, Wu, Yi, Sreenath, Koushil
Model-free reinforcement learning is a promising approach for autonomously solving challenging robotics control problems, but faces exploration difficulty without information of the robot's kinematics and dynamics morphology. The under-exploration of
Externí odkaz:
http://arxiv.org/abs/2403.17320
Autor:
Li, Chu, Zhang, Zhihan, Saugstad, Michael, Safranchik, Esteban, Kulkarni, Minchu, Huang, Xiaoyu, Patel, Shwetak, Iyer, Vikram, Althoff, Tim, Froehlich, Jon E.
Crowdsourcing platforms have transformed distributed problem-solving, yet quality control remains a persistent challenge. Traditional quality control measures, such as prescreening workers and refining instructions, often focus solely on optimizing e
Externí odkaz:
http://arxiv.org/abs/2403.09810
Publikováno v:
JMIR Medical Informatics, Vol 8, Iss 4, p e16749 (2020)
BackgroundRecent research in machine-learning techniques has led to significant progress in various research fields. In particular, knowledge discovery using this method has become a hot topic in traditional Chinese medicine. As the key clinical ma
Externí odkaz:
https://doaj.org/article/728f20a6ccc148f4bfc702629fc7bd93
Publikováno v:
Chinese Management Studies, 2024, Vol. 18, Issue 6, pp. 1800-1816.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/CMS-02-2023-0059
We present Skill Transformer, an approach for solving long-horizon robotic tasks by combining conditional sequence modeling and skill modularity. Conditioned on egocentric and proprioceptive observations of a robot, Skill Transformer is trained end-t
Externí odkaz:
http://arxiv.org/abs/2308.09873
Autor:
Huang, Xiaoyu
In this paper, we study Fontaine-Laffaille, self-dual deformations of a mod p non-semisimple Galois representation of dimension n with its Jordan-Holder factors being three mutually non-isomorphic absolutely irreducible representations. We show that
Externí odkaz:
http://arxiv.org/abs/2308.02708
Autor:
Yao, Shanliang, Guan, Runwei, Huang, Xiaoyu, Li, Zhuoxiao, Sha, Xiangyu, Yue, Yong, Lim, Eng Gee, Seo, Hyungjoon, Man, Ka Lok, Zhu, Xiaohui, Yue, Yutao
Publikováno v:
IEEE Transactions on Intelligent Vehicles 2023
Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surrounding environment for safe and efficient navigation. To achieve accurate
Externí odkaz:
http://arxiv.org/abs/2304.10410