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20212026
most citedVisual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions

38 citations · 49 across the 7 of their papers we have counts for

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Showing 2023Show all

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cs.RO2023★ 38 cited

Visual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions

André Yuji Yasutomi, Hideyuki Ichiwara, Hiroshi Ito +2

Anchor-bolt insertion is a peg-in-hole task performed in the construction field for holes in concrete. Efforts have been made to automate this task, but the variable lighting and h…

cs.RO2023

Real-time Motion Generation and Data Augmentation for Grasping Moving Objects with Dynamic Speed and Position Changes

Kenjiro Yamamoto, Hiroshi Ito, Hideyuki Ichiwara +2

While deep learning enables real robots to perform complex tasks had been difficult to implement in the past, the challenge is the enormous amount of trial-and-error and motion tea…