Doyoon Kong

dblp:403/7105 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0005-0669-9160ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot navigation and mapping · 44% 3D vision · 44% Deep learning architectures and training · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › motion estimation › ego-motion estimation
monocular visual-inertial odometry
1.012026
Fast and Robust Online Initialization of Monocular Visual-Inertial Odometry via One-Dimensional Cost Approximation · IEEE Trans. Robotics 2026
Robotics › Robot navigation and mapping › visual odometry
visual-inertial odometry
1.012026
Fast and Robust Online Initialization of Monocular Visual-Inertial Odometry via One-Dimensional Cost Approximation · IEEE Trans. Robotics 2026
Machine learning › Deep learning architectures and training
weight initialization
0.312026
Fast and Robust Online Initialization of Monocular Visual-Inertial Odometry via One-Dimensional Cost Approximation · IEEE Trans. Robotics 2026

Methods — techniques the papers use, named apart from their topics

one-dimensional cost approximation · 1.0
YearPublicationVenuePosition
2026 Fast and Robust Online Initialization of Monocular Visual-Inertial Odometry via One-Dimensional Cost Approximation
Jiseock Kang, Jaeu Choe, Doyoon Kong, Byoungkwon Yoon, Jaehwi Cho
IEEE Trans. Robotics3
2025 Wrench Control of Dual-Arm Robot on Flexible Base With Supporting Contact Surface
abstract
We propose a novel high-force/high-precision interaction control framework of a dual-arm robot system on a flexible base, with one arm holding, or making contact with, a supporting surface, while the other arm can exert any arbitrary wrench in a certain polytope through a desired pose against environments or objects. Our proposed framework can achieve high-force/precision tasks by utilizing the supporting surface just as we humans do while taking into account various important constraints (e.g., system stability, joint angle/torque limits, friction-cone constraint, etc.) and the passive compliance of the flexible base. We first design the control as a combination of: 1) nominal control; 2) active stiffness control; and 3) feedback wrench control. We then sequentially perform optimizations of the nominal configuration (and its related wrenches) and the active stiffness control gain. We also design the proportional–integral type feedback wrench control to improve the robustness and precision of the control. The key theoretical enabler for our framework is a novel stiffness analysis of the dual-arm system with flexibility, which, when combined with certain constraints, provides some peculiar relations, that can effectively be used to significantly simplify the optimization problem-solving and to facilitate the feedback wrench control design by manifesting the compliance relation at the interaction port. The efficacy of the theory is then validated and demonstrated through simulations and experiments.
Jeongseob Lee, Doyoon Kong, Hojun Cha, Jeongmin Lee 0002, Dongseok Ryu, Hocheol Shin
IEEE Trans. Robotics2