Seunghoon Shin — accepted AI-conference papers

2021

Design of a Compact Embedded Hydraulic Power Unit for Bipedal Robots

Buyoun Cho, Min-Su Kim, Sung-Woo Kim, Seunghoon Shin, Yeseong Jeong, Jun-Ho Oh +1

RA-L 2021

This letter proposes a design method of a compact embedded hydraulic power unit (HPU) for a bipedal robot and a controller to regulate the supply pressure. The HPU consists of an integrated pump-motor unit. The unit is immersed in hydraulic oil for efficient space utilization and heat dissipation fr

Cited by 16 Source ↗Scholar ↗

2021

Force Control of a Hydraulic Actuator With a Neural Network Inverse Model

Sung-Woo Kim, Buyoun Cho, Seunghoon Shin, Jun-Ho Oh, Jemin Hwangbo, Hae-Won Park

RA-L 2021

In this study, a learning-based force controller for a hydraulic actuator is presented. We propose a control method with an inverse model composed of a deep neural network, which accurately tracks a force trajectory. This learning-based controller can be trained offline using force and position data

Cited by 38 Source ↗Scholar ↗