Yuki Suga — accepted AI-conference papers

2024

Augmenting Compliance With Motion Generation Through Imitation Learning Using Drop-Stitch Reinforced Inflatable Robot Arm With Rigid Joints

Gangadhara Naga Sai Gubbala, Masato Nagashima, Hiroki Mori, Young Ah Seong, Hiroki Sato, Ryuma Niiyama +2

RA-L 2024

Safe physical human-robot collaboration is possible with soft robots due to their inherent compliance and low inertia. Soft bodies inherently possess passive compliance, providing adaptability in collaborative tasks because of their deformations; however, the same features add complexity to modeling

Cited by 7 Source ↗Scholar ↗

2021

In-air Knotting of Rope using Dual-Arm Robot based on Deep Learning

Kanata Suzuki, Momomi Kanamura, Yuki Suga, Hiroki Mori, Tetsuya Ogata

IROS 2021poster

In this study, we report the successful execution of in-air knotting of rope using a dual-arm two-finger robot based on deep learning. Owing to its flexibility, the state of the rope was in constant flux during the operation of the robot. This required the robot control system to dynamically corresp…

Cited by 32 Source ↗Scholar ↗

2018

Large Range Impedance Shaping for Physical Human Robot Interaction Through Light Quantity Measurement Based Torque Regulation

Wei Wang, Chang Wei, Yuki Suga, Chiahao Kuo, Alexander Schmitz, Shigeki Sugano

RA-L 2018

Impedance shaping is a fundamental requirement for physical human-robot interaction. In order to achieve a large range impedance capability, light quantity measurement based torque feedback regulation has been introduced, based on which a stiff actuator design can be realized with reliable torque me

Cited by 1 Source ↗Scholar ↗