activity
20192024
most citedMulti-Fingered In-Hand Manipulation with Various Object Properties Using Graph Convolutional Networks and Distributed Tactile Sensors

50 citations · 127 across the 16 of their papers we have counts for

collaborators
Showing 2023Show all

6 papers · 1 filter

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…

cs.RO2023★ 2 cited

Learning Multimodal Attention for Manipulating Deformable Objects with Changing States

Namiko Saito, Mayu Tatsumi, Ayuna Kubo +4

To support humans in their daily lives, robots are required to autonomously learn, adapt to objects and environments, and perform the appropriate actions. We tackled on the task of…

cs.RO2023

Interactively Robot Action Planning with Uncertainty Analysis and Active Questioning by Large Language Model

Kazuki Hori, Kanata Suzuki, Tetsuya Ogata

The application of the Large Language Model (LLM) to robot action planning has been actively studied. The instructions given to the LLM by natural language may include ambiguity an…

cs.RO2023★ 6 cited

Deep Predictive Learning: Motion Learning Concept inspired by Cognitive Robotics

Kanata Suzuki, Hiroshi Ito, Tatsuro Yamada +2

Bridging the gap between motion models and reality is crucial by using limited data to deploy robots in the real world. Deep learning is expected to be generalized to diverse situa…

cs.RO2023

Force Map: Learning to Predict Contact Force Distribution from Vision

Ryo Hanai, Yukiyasu Domae, Ixchel G. Ramirez-Alpizar +2

When humans see a scene, they can roughly imagine the forces applied to objects based on their experience and use them to handle the objects properly. This paper considers transfer…