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pro vyhledávání: '"Zhang, Zhengshen"'
Autor:
Zhang, Zhengshen, Zhou, Lei, Liu, Chenchen, Liu, Zhiyang, Yuan, Chengran, Guo, Sheng, Zhao, Ruiteng, Ang Jr., Marcelo H., Tay, Francis EH
The versatility and adaptability of human grasping catalyze advancing dexterous robotic manipulation. While significant strides have been made in dexterous grasp generation, current research endeavors pivot towards optimizing object manipulation whil
Externí odkaz:
http://arxiv.org/abs/2407.09899
Autor:
Zhou, Lei, Wang, Haozhe, Zhang, Zhengshen, Liu, Zhiyang, Tay, Francis EH, Ang. Jr, adn Marcelo H.
In the realm of robotic grasping, achieving accurate and reliable interactions with the environment is a pivotal challenge. Traditional methods of grasp planning methods utilizing partial point clouds derived from depth image often suffer from reduce
Externí odkaz:
http://arxiv.org/abs/2404.03462
In this work, we present SynTable, a unified and flexible Python-based dataset generator built using NVIDIA's Isaac Sim Replicator Composer for generating high-quality synthetic datasets for unseen object amodal instance segmentation of cluttered tab
Externí odkaz:
http://arxiv.org/abs/2307.07333
Autor:
Su, Ruidan, Liu, Han, Zhang, Zhengshen, Wang, Haozhe, Zhou, Lei, Liu, Zhiyang, Liu, Chenchen, Tay, Francis EH, Lu, Wen Feng, Ang, Marcelo H.
Publikováno v:
Proceedings of SPIE; March 2024, Vol. 13074 Issue: 1 p130740L-130740L-5, 1176666p