Ji Ho Kwak — accepted AI-conference papers

2022

Semantic Grasping Via a Knowledge Graph of Robotic Manipulation: A Graph Representation Learning Approach

Ji Ho Kwak, Jaejun Lee, Joyce Jiyoung Whang, Sungho Jo

RA-L 2022

Semantic grasping aims to make stable robotic grasps suitable for specific object manipulation tasks. While existing semantic grasping models focus only on the grasping regions of objects based on their affordances, reasoning about which gripper to use for grasping, e.g., a rigid parallel-jaw grippe

Cited by 25 Source ↗Scholar ↗

2021

Affect-driven Robot Behavior Learning System using EEG Signals for Less Negative Feelings and More Positive Outcomes

Byung Hyung Kim, Ji Ho Kwak, Minuk Kim, Sungho Jo

IROS 2021poster

Learning from human feedback using event-related electroencephalography (EEG) signals has attracted extensive attention recently owing to their intuitive communication ability by decoding user intentions. However, this approach requires users to perform specified tasks and their success or failure.…

Cited by 2 Source ↗Scholar ↗