Chanyoung Jung — accepted AI-conference papers

2023

Adaptive Keyframe Generation based LiDAR Inertial Odometry for Complex Underground Environments

Boseong Kim, Chanyoung Jung, D. Hyunchul Shim, Ali–akbar Agha–mohammadi

ICRA 2023poster

In this paper, we present a LiDAR Inertial Odometry (LIO) algorithm utilizing adaptive keyframe generation which achieves fast and accurate state estimation for aerial and ground robots. It is known that keyframe generation significantly affects the performance of Simultaneous Localization and Mappi…

Cited by 18 Source ↗Scholar ↗

2021

Incorporating Multi-Context Into the Traversability Map for Urban Autonomous Driving Using Deep Inverse Reinforcement Learning

Chanyoung Jung, David Hyunchul Shim

RA-L 2021

Autonomous driving in an urban environment with surrounding agents remains challenging. One of the key challenges is to accurately predict the traversability map that probabilistically represents future trajectories considering multiple contexts: inertial, environmental, and social. To address this,

Cited by 29 Source ↗Scholar ↗