50 citations · 100 across the 2 of their papers we have counts for
4 papers · 1 filter
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…
Multi-Fingered In-Hand Manipulation with Various Object Properties Using Graph Convolutional Networks and Distributed Tactile Sensors
Satoshi Funabashi, Tomoki Isobe, Fei Hongyi +4
Multi-fingered hands could be used to achieve many dexterous manipulation tasks, similarly to humans, and tactile sensing could enhance the manipulation stability for a variety of…
How to select and use tools? : Active Perception of Target Objects Using Multimodal Deep Learning
Namiko Saito, Tetsuya Ogata, Satoshi Funabashi +2
Selection of appropriate tools and use of them when performing daily tasks is a critical function for introducing robots for domestic applications. In previous studies, however, ad…
Detecting Features of Tools, Objects, and Actions from Effects in a Robot using Deep Learning
Namiko Saito, Kitae Kim, Shingo Murata +2
We propose a tool-use model that can detect the features of tools, target objects, and actions from the provided effects of object manipulation. We construct a model that enables r…