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Eungchang Mason Lee

11 accepted papers

2026

AIM-SLAM: Dense Monocular SLAM Via Adaptive and Informative Multi-View Keyframe Prioritization with Foundation Model

ICRA 2026poster

Recent advances in geometric foundation models have emerged as a promising alternative for addressing the challenge of dense reconstruction in monocular visual simultaneous localization and mapping (SLAM). Although geometric foundation models enable SLAM to leverage variable input views, the previou…

2026

GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow

RA-L 2026

Gaussian splatting has recently gained traction as a compelling map representation for SLAM systems, enabling dense and photo-realistic scene modeling. However, its application to monocular SLAM remains challenging due to the lack of reliable geometric cues from monocular input. Without geometric su

Cited by 0SourcecodeScholar
2026

LODESTAR: Degeneracy-Aware LiDAR-Inertial Odometry With Adaptive Schmidt-Kalman Filter and Data Exploitation

RA-L 2026

LiDAR-inertial odometry (LIO) has been widely used in robotics due to its high accuracy. However, its performance degrades in degenerate environments, such as long corridors and high-altitude flights, where LiDAR measurements are imbalanced or sparse, leading to ill-posed state estimation. In this l

Cited by 3SourceScholar
2025

SaWa-ML: Structure-Aware Pose Correction and Weight Adaptation-Based Robust Multi-Robot Localization

IROS 2025

Multi-robot localization is a crucial task for implementing multi-robot systems. Numerous researchers have proposed optimization-based multi-robot localization methods that use camera, IMU, and UWB sensors. Nevertheless, characteristics of individual robot odometry estimates and distance measurement

Cited by 0SourceScholar
2023

Enhancing Robustness of Line Tracking Through Semi-Dense Epipolar Search in Line-Based SLAM

IROS 2023poster

Line information from urban structures can be exploited as an additional geometrical feature to achieve robust vision-based simultaneous localization and mapping (SLAM) systems in textureless scenes. Sometimes, however, conventional line tracking methods fail to track caused by image blur or occlusi…

Cited by 1SourceScholar
2022

Retro-RL: Reinforcing Nominal Controller With Deep Reinforcement Learning for Tilting-Rotor Drones

RA-L 2022

Studies that broaden drone applications into complex tasks require a stable control framework. Recently, deep reinforcement learning (RL) algorithms have been exploited in many studies for robot control to accomplish complex tasks. Unfortunately, deep RL algorithms might not be suitable for being de

Cited by 13SourceScholar
2022

STEP: State Estimator for Legged Robots Using a Preintegrated Foot Velocity Factor

RA-L 2022

Wepropose a novel state estimator for legged robots, <i>STEP</i>, achieved through a novel preintegrated foot velocity factor. In the preintegrated foot velocity factor, the usual non-slip assumption is not adopted. Instead, the end effector velocity becomes observable by exploiting the body speed o

Cited by 39SourceScholar
2022

TRAVEL: Traversable Ground and Above-Ground Object Segmentation Using Graph Representation of 3D LiDAR Scans

RA-L 2022

Perception of traversable regions and objects of interest from a 3D point cloud is one of the critical tasks in autonomous navigation. A ground vehicle needs to look for traversable terrains that are explorable by wheels. Then, to make safe navigation decisions, the segmentation of objects positione

Cited by 55SourcecodeScholar
2021

Corrections to "Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle"

RA-L 2021

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Cited by 0SourceScholar
2021

REAL: Rapid Exploration with Active Loop-Closing toward Large-Scale 3D Mapping using UAVs

IROS 2021poster

Exploring an unknown environment without colliding with obstacles is one of the essentials of autonomous vehicles to perform diverse missions such as structural inspections, rescues, deliveries, and so forth. Therefore, unmanned aerial vehicles (UAVS), which are fast, agile, and have high degrees of…

Cited by 41SourcecodeScholar
2021

Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle

RA-L 2021

This letter presents benchmark tests of various visual(-inertial) odometry algorithms on NVIDIA Jetson platforms. The compared algorithms include mono and stereo, covering Visual Odometry (VO) and Visual-Inertial Odometry (VIO): VINS-Mono, VINS-Fusion, Kimera, ALVIO, Stereo-MSCKF, ORB-SLAM2 stereo,

Cited by 70SourcecodeScholar