Zobrazeno 1 - 10
of 146
pro vyhledávání: '"Luo Zhengyi"'
Publikováno v:
National Science Open, Vol 3 (2023)
In order to increase the renewable energy penetration for building and industrial energy use in industrial parks, the energy supply system requires transforming from a centralized energy supply mode to a distributed + centralized energy supply mode.
Externí odkaz:
https://doaj.org/article/9e9ced441f734f0eb16c3ceb5bdd9ed6
Autor:
He, Tairan, Xiao, Wenli, Lin, Toru, Luo, Zhengyi, Xu, Zhenjia, Jiang, Zhenyu, Kautz, Jan, Liu, Changliu, Shi, Guanya, Wang, Xiaolong, Fan, Linxi, Zhu, Yuke
Humanoid whole-body control requires adapting to diverse tasks such as navigation, loco-manipulation, and tabletop manipulation, each demanding a different mode of control. For example, navigation relies on root velocity tracking, while tabletop mani
Externí odkaz:
http://arxiv.org/abs/2410.21229
Understanding how humans interact with each other is key to building realistic multi-human virtual reality systems. This area remains relatively unexplored due to the lack of large-scale datasets. Recent datasets focusing on this issue mainly consist
Externí odkaz:
http://arxiv.org/abs/2410.20294
Autor:
Tevet, Guy, Raab, Sigal, Cohan, Setareh, Reda, Daniele, Luo, Zhengyi, Peng, Xue Bin, Bermano, Amit H., van de Panne, Michiel
Motion diffusion models and Reinforcement Learning (RL) based control for physics-based simulations have complementary strengths for human motion generation. The former is capable of generating a wide variety of motions, adhering to intuitive control
Externí odkaz:
http://arxiv.org/abs/2410.03441
Autor:
Wang, Yinhuai, Zhao, Qihan, Yu, Runyi, Zeng, Ailing, Lin, Jing, Luo, Zhengyi, Tsui, Hok Wai, Yu, Jiwen, Li, Xiu, Chen, Qifeng, Zhang, Jian, Zhang, Lei, Tan, Ping
Mastering basketball skills such as diverse layups and dribbling involves complex interactions with the ball and requires real-time adjustments. Traditional reinforcement learning methods for interaction skills rely on labor-intensive, manually desig
Externí odkaz:
http://arxiv.org/abs/2408.15270
We present a method for controlling a simulated humanoid to grasp an object and move it to follow an object trajectory. Due to the challenges in controlling a humanoid with dexterous hands, prior methods often use a disembodied hand and only consider
Externí odkaz:
http://arxiv.org/abs/2407.11385
Autor:
Luo, Zhengyi, Wang, Jiashun, Liu, Kangni, Zhang, Haotian, Tessler, Chen, Wang, Jingbo, Yuan, Ye, Cao, Jinkun, Lin, Zihui, Wang, Fengyi, Hodgins, Jessica, Kitani, Kris
We present SMPLOlympics, a collection of physically simulated environments that allow humanoids to compete in a variety of Olympic sports. Sports simulation offers a rich and standardized testing ground for evaluating and improving the capabilities o
Externí odkaz:
http://arxiv.org/abs/2407.00187
Autor:
He, Tairan, Luo, Zhengyi, He, Xialin, Xiao, Wenli, Zhang, Chong, Zhang, Weinan, Kitani, Kris, Liu, Changliu, Shi, Guanya
We present OmniH2O (Omni Human-to-Humanoid), a learning-based system for whole-body humanoid teleoperation and autonomy. Using kinematic pose as a universal control interface, OmniH2O enables various ways for a human to control a full-sized humanoid
Externí odkaz:
http://arxiv.org/abs/2406.08858
We address the challenge of content diversity and controllability in pedestrian simulation for driving scenarios. Recent pedestrian animation frameworks have a significant limitation wherein they primarily focus on either following trajectory [46] or
Externí odkaz:
http://arxiv.org/abs/2404.19722
Autor:
Luo, Zhengyi, Cao, Jinkun, Khirodkar, Rawal, Winkler, Alexander, Huang, Jing, Kitani, Kris, Xu, Weipeng
We present SimXR, a method for controlling a simulated avatar from information (headset pose and cameras) obtained from AR / VR headsets. Due to the challenging viewpoint of head-mounted cameras, the human body is often clipped out of view, making tr
Externí odkaz:
http://arxiv.org/abs/2403.06862