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Shun Ogasa

4 accepted papers

2020

Stable In-Grasp Manipulation with a Low-Cost Robot Hand by Using 3-Axis Tactile Sensors with a CNN

Satoshi Funabashi, Tomoki Isobe, Shun Ogasa, Tetsuya Ogata, Alexander Schmitz, Tito Pradhono Tomo +1
IROS 2020poster

The use of tactile information is one of the most important factors for achieving stable in-grasp manipulation. Especially with low-cost robotic hands that provide low-precision control, robust in-grasp manipulation is challenging. Abundant tactile information could provide the required feed-back to…

Cited by 23Source ↗Scholar ↗
2020

Variable In-Hand Manipulations for Tactile-Driven Robot Hand via CNN-LSTM

Satoshi Funabashi, Shun Ogasa, Tomoki Isobe, Tetsuya Ogata, Alexander Schmitz, Tito Pradhono Tomo +1
IROS 2020poster

Performing various in-hand manipulation tasks, without learning each individual task, would enable robots to act more versatile, while reducing the effort for training. However, in general it is difficult to achieve stable in-hand manipulation, because the contact state between the fingertips become…

Cited by 16Source ↗Scholar ↗
2019

Sequential clustering for tactile image compression to enable direct adaptive feedback

Andreas Geier, Gang Yan, Tito Pradhono Tomo, Shun Ogasa, Sophon Somlor, Alexander Schmitz +1
IROS 2019poster

The sense of touch is often crucial for humans to perform manipulation tasks. Providing tactile feedback during teleoperation or for users of prosthetic devices would be beneficial. However, the representation of tactile information constitutes a major technical challenge, since the numerous and pos…

Cited by 1Source ↗Scholar ↗
2018

Object Recognition Through Active Sensing Using a Multi-Fingered Robot Hand with 3D Tactile Sensors

Satoshi Funabashi, Shu Morikuni, Andreas Geier, Alexander Schmitz, Shun Ogasa, Tito Pradhono Torno +2
IROS 2018poster

This paper investigates tactile object recognition with relatively densely distributed force vector measurements and evaluates what kind of tactile information is beneficial for object recognition. The uSkin tactile sensors are embedded in an Allegro Hand, and provide 240 triaxial force vector measu…

Cited by 57Source ↗Scholar ↗