Zobrazeno 1 - 10
of 3 135
pro vyhledávání: '"Xian ZHOU"'
Autor:
Wang, Yian, Qiu, Xiaowen, Liu, Jiageng, Chen, Zhehuan, Cai, Jiting, Wang, Yufei, Wang, Tsun-Hsuan, Xian, Zhou, Gan, Chuang
Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generation, diffusion-based scene generation, and large language model (LLM)
Externí odkaz:
http://arxiv.org/abs/2411.09823
In this work, we aim to teach robots to manipulate various thin-shell materials. Prior works studying thin-shell object manipulation mostly rely on heuristic policies or learn policies from real-world video demonstrations, and only focus on limited m
Externí odkaz:
http://arxiv.org/abs/2404.00451
We introduce DIFFTACTILE, a physics-based differentiable tactile simulation system designed to enhance robotic manipulation with dense and physically accurate tactile feedback. In contrast to prior tactile simulators which primarily focus on manipula
Externí odkaz:
http://arxiv.org/abs/2403.08716
Autor:
Wang, Yufei, Sun, Zhanyi, Zhang, Jesse, Xian, Zhou, Biyik, Erdem, Held, David, Erickson, Zackory
Reward engineering has long been a challenge in Reinforcement Learning (RL) research, as it often requires extensive human effort and iterative processes of trial-and-error to design effective reward functions. In this paper, we propose RL-VLM-F, a m
Externí odkaz:
http://arxiv.org/abs/2402.03681
Autor:
Wang, Yufei, Xian, Zhou, Chen, Feng, Wang, Tsun-Hsuan, Wang, Yian, Fragkiadaki, Katerina, Erickson, Zackory, Held, David, Gan, Chuang
We present RoboGen, a generative robotic agent that automatically learns diverse robotic skills at scale via generative simulation. RoboGen leverages the latest advancements in foundation and generative models. Instead of directly using or adapting t
Externí odkaz:
http://arxiv.org/abs/2311.01455
Generalist robot manipulators need to learn a wide variety of manipulation skills across diverse environments. Current robot training pipelines rely on humans to provide kinesthetic demonstrations or to program simulation environments and to code up
Externí odkaz:
http://arxiv.org/abs/2310.18308
Publikováno v:
IET Image Processing, Vol 18, Iss 13, Pp 4328-4340 (2024)
Abstract Due to the powerful ability in capturing the global information, transformer has become an alternative architecture of CNNs for hyperspectral image classification. However, general transformer mainly considers the global spectral information
Externí odkaz:
https://doaj.org/article/9173a33cd3374f848168917aa44cffee
Autor:
Xiaowei Tang, Ping Wang, Shu Huang, Jieyu Peng, Wei Zhang, Xiaomin Shi, Lei Shi, Xiaolin Zhong, Muhan Lyu, Xian Zhou, Enqiang Linghu, Jinjiao Li, Yuanyuan Ji
Publikováno v:
Chinese Medical Journal, Vol 137, Iss 19, Pp 2358-2368 (2024)
Abstract. Background:. China is one of the countries with the largest burden of gastrointestinal and liver diseases (GILD) in the world. The GILD constitutes various causes of mortality and disability. The study aimed to investigate the trend of GILD
Externí odkaz:
https://doaj.org/article/9e03d46c82884882b955bfb76a77558b
3D perceptual representations are well suited for robot manipulation as they easily encode occlusions and simplify spatial reasoning. Many manipulation tasks require high spatial precision in end-effector pose prediction, which typically demands high
Externí odkaz:
http://arxiv.org/abs/2306.17817
This document serves as a position paper that outlines the authors' vision for a potential pathway towards generalist robots. The purpose of this document is to share the excitement of the authors with the community and highlight a promising research
Externí odkaz:
http://arxiv.org/abs/2305.10455