Byeongdo Lim — accepted AI-conference papers

2024

EquiGraspFlow: SE(3)-Equivariant 6-DoF Grasp Pose Generative Flows

Byeongdo Lim, Jongmin Kim, Jihwan Kim, Yonghyeon Lee, Frank C. Park

CoRL 2024poster

Traditional methods for synthesizing 6-DoF grasp poses from 3D observations often rely on geometric heuristics, resulting in poor generalizability, limited grasp options, and higher failure rates. Recently, data-driven methods have been proposed that use generative models to learn the distribution o…

Cited by 7 Source ↗code ↗Scholar ↗

2022

SE(2)-Equivariant Pushing Dynamics Models for Tabletop Object Manipulations

Seungyeon Kim, Byeongdo Lim, Yonghyeon Lee, Frank C. Park

CoRL 2022oral

For tabletop object manipulation tasks, learning an accurate pushing dynamics model, which predicts the objects' motions when a robot pushes an object, is very important. In this work, we claim that an ideal pushing dynamics model should have the SE(2)-equivariance property, i.e., if tabletop object…

Cited by 13 Source ↗code ↗Scholar ↗