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

Ning Guo, Xudong Han, Xiaobo Liu, Shuqiao Zhong, Zhiyuan Zhou, Jian Lin, Jian S. Dai, Fang Wan, Chaoyang Song

Year
2024
Citations
4
Access
Open access

Abstract

Underwater Grasping Thanks to a breakthrough in soft robotics and AI, robots can now “feel” their way through underwater environments by learning from grasping on land. Using a high-frame-rate camera and a soft, omnidirectional adaptive finger, this pioneering work demonstrates a robot learning system to precisely grasp objects underwater, even in low-visibility conditions. This new “touch” technology unlocks exciting possibilities for underwater exploration and scientific discovery, allowing robots to interact with delicate objects and navigate challenging environments with much-enhanced reliability and robustness. For further details, see article number 2300382 by Fang Wan, Chaoyang Song, and co-workers.

Keywords

UnderwaterComputer sciencePsychologyGeographyArchaeology

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