Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Qin, Yuzhe"'
Autor:
Tao, Stone, Xiang, Fanbo, Shukla, Arth, Qin, Yuzhe, Hinrichsen, Xander, Yuan, Xiaodi, Bao, Chen, Lin, Xinsong, Liu, Yulin, Chan, Tse-kai, Gao, Yuan, Li, Xuanlin, Mu, Tongzhou, Xiao, Nan, Gurha, Arnav, Huang, Zhiao, Calandra, Roberto, Chen, Rui, Luo, Shan, Su, Hao
Simulation has enabled unprecedented compute-scalable approaches to robot learning. However, many existing simulation frameworks typically support a narrow range of scenes/tasks and lack features critical for scaling generalizable robotics and sim2re
Externí odkaz:
http://arxiv.org/abs/2410.00425
Autor:
Yang, Shiqi, Liu, Minghuan, Qin, Yuzhe, Ding, Runyu, Li, Jialong, Cheng, Xuxin, Yang, Ruihan, Yi, Sha, Wang, Xiaolong
Learning from demonstrations has shown to be an effective approach to robotic manipulation, especially with the recently collected large-scale robot data with teleoperation systems. Building an efficient teleoperation system across diverse robot plat
Externí odkaz:
http://arxiv.org/abs/2408.11805
Autor:
Ding, Runyu, Qin, Yuzhe, Zhu, Jiyue, Jia, Chengzhe, Yang, Shiqi, Yang, Ruihan, Qi, Xiaojuan, Wang, Xiaolong
Teleoperation is a crucial tool for collecting human demonstrations, but controlling robots with bimanual dexterous hands remains a challenge. Existing teleoperation systems struggle to handle the complexity of coordinating two hands for intricate ma
Externí odkaz:
http://arxiv.org/abs/2407.03162
Autor:
Xie, Pengwei, Chen, Rui, Chen, Siang, Qin, Yuzhe, Xiang, Fanbo, Sun, Tianyu, Xu, Jing, Wang, Guijin, Su, Hao
Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots. Existing learning-based solutions mainly focus on visual affordance learning or other pre-trained visual models to guide manipulation
Externí odkaz:
http://arxiv.org/abs/2404.17302
Autor:
Su, Entong, Jia, Chengzhe, Qin, Yuzhe, Zhou, Wenxuan, Macaluso, Annabella, Huang, Binghao, Wang, Xiaolong
Using tactile sensors for manipulation remains one of the most challenging problems in robotics. At the heart of these challenges is generalization: How can we train a tactile-based policy that can manipulate unseen and diverse objects? In this paper
Externí odkaz:
http://arxiv.org/abs/2403.12170
Autor:
Wang, Jun, Qin, Yuzhe, Kuang, Kaiming, Korkmaz, Yigit, Gurumoorthy, Akhilan, Su, Hao, Wang, Xiaolong
We introduce CyberDemo, a novel approach to robotic imitation learning that leverages simulated human demonstrations for real-world tasks. By incorporating extensive data augmentation in a simulated environment, CyberDemo outperforms traditional in-d
Externí odkaz:
http://arxiv.org/abs/2402.14795
The sense of touch is an essential ability for skillfully performing a variety of tasks, providing the capacity to search and manipulate objects without relying on visual information. Extensive research has been conducted over time to apply these hum
Externí odkaz:
http://arxiv.org/abs/2401.12496
Autor:
Yuan, Ying, Che, Haichuan, Qin, Yuzhe, Huang, Binghao, Yin, Zhao-Heng, Lee, Kang-Won, Wu, Yi, Lim, Soo-Chul, Wang, Xiaolong
Executing contact-rich manipulation tasks necessitates the fusion of tactile and visual feedback. However, the distinct nature of these modalities poses significant challenges. In this paper, we introduce a system that leverages visual and tactile se
Externí odkaz:
http://arxiv.org/abs/2312.01853
Autor:
Wang, Lirui, Ling, Yiyang, Yuan, Zhecheng, Shridhar, Mohit, Bao, Chen, Qin, Yuzhe, Wang, Bailin, Xu, Huazhe, Wang, Xiaolong
Publikováno v:
International Conference on Learning Representations (ICLR), 2024
Collecting large amounts of real-world interaction data to train general robotic policies is often prohibitively expensive, thus motivating the use of simulation data. However, existing methods for data generation have generally focused on scene-leve
Externí odkaz:
http://arxiv.org/abs/2310.01361
Autor:
Huang, Binghao, Chen, Yuanpei, Wang, Tianyu, Qin, Yuzhe, Yang, Yaodong, Atanasov, Nikolay, Wang, Xiaolong
Humans throw and catch objects all the time. However, such a seemingly common skill introduces a lot of challenges for robots to achieve: The robots need to operate such dynamic actions at high-speed, collaborate precisely, and interact with diverse
Externí odkaz:
http://arxiv.org/abs/2309.05655