Autoencoding a Soft Touch to Learn Grasping from On‐Land to Underwater

Autoencoding a Soft Touch to Learn Grasping from On‐Land to Underwater

Robots play a critical role as the physical agent of human operators in exploring the ocean. However, it remains challenging to grasp objects reliably while fully submerging under a highly pressurized aquatic environment with little visible light, mainly due to the fluidic interference on the tactil...

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Bibliographic Details
Main Authors: Ning Guo, Xudong Han, Xiaobo Liu, Shuqiao Zhong, Zhiyuan Zhou, Jian Lin, Jiansheng Dai, Fang Wan, Chaoyang Song
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Advanced Intelligent Systems
Subjects:
soft robotics
tactile learning
underwater grasping
Online Access:https://doi.org/10.1002/aisy.202300382

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