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pro vyhledávání: '"Xu, Zhengtong"'
Autor:
Xu, Zhengtong, Uppuluri, Raghava, Zhang, Xinwei, Fitch, Cael, Crandall, Philip Glen, Shou, Wan, Wang, Dongyi, She, Yu
UniT is a novel approach to tactile representation learning, using VQVAE to learn a compact latent space and serve as the tactile representation. It uses tactile images obtained from a single simple object to train the representation with transferabi
Externí odkaz:
http://arxiv.org/abs/2408.06481
Autor:
Xu, Zhengtong, She, Yu
Grasping is a crucial task in robotics, necessitating tactile feedback and reactive grasping adjustments for robust grasping of objects under various conditions and with differing physical properties. In this paper, we introduce LeTac-MPC, a learning
Externí odkaz:
http://arxiv.org/abs/2403.04934
Autor:
Xu, Zhengtong, She, Yu
This paper introduces LeTO, a method for learning constrained visuomotor policy with differentiable trajectory optimization. Our approach integrates a differentiable optimization layer into the neural network. By formulating the optimization layer as
Externí odkaz:
http://arxiv.org/abs/2401.17500
Akademický článek
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Publikováno v:
IEEE Sensors Journal; October 2023, Vol. 23 Issue: 20 p25440-25450, 11p
