Woosik Lee

Woosik Lee
University of Delaware | UDel UD · Department of Mechanical Engineering

MS

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13
Publications
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304
Citations

Publications

Publications (13)
Article
Full-text available
When studying the right invariant error states for consistent visual-inertial navigation system (VINS), we discover that although invariant extended Kalman filter (EKF) based VINS can consistently model system uncertainties, the features in the state can cause high computational cost in state covariance propagation compared to the standard EKF. To...
Conference Paper
Full-text available
In this paper, we introduce a novel visual-inertial-wheel odometry (VIWO) system for ground vehicles, which efficiently fuses multi-modal visual, inertial and 2D wheel odometry measurements in a sliding-window filtering fashion. As multi-sensor fusion requires both intrinsic and extrinsic (spatiotemproal) calibration parameters which may vary over...
Conference Paper
Full-text available
In this paper, we present an open platform, termed OpenVINS, for visual-inertial estimation research for both the academic community and practitioners from industry. The open sourced codebase provides a foundation for researchers and engineers to quickly start developing new capabilities for their visual-inertial systems. This codebase has out of t...
Conference Paper
Full-text available
In this paper, we present an efficient and robust GPS-aided visual inertial odometry (GPS-VIO) system that fuses IMU-camera data with intermittent GPS measurements. To perform sensor fusion, spatiotemporal sensor calibration and initialization of the transform between the sensor reference frames are required. We propose an online calibration method...
Article
Full-text available
Autonomous navigation technology is used in various applications, such as agricultural robots and autonomous vehicles. The key technology for autonomous navigation is ego-motion estimation, which uses various sensors. Wheel encoders and global navigation satellite systems (GNSSs) are widely used in localization for autonomous vehicles, and there ar...
Conference Paper
This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual features, and extracted LiDAR points. In particular, the proposed LIC-Fusion performs online spatial and temporal sensor calibration between all three asynchronous sensors, in...
Preprint
Full-text available
This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual features, and extracted LiDAR points. In particular, the proposed LIC-Fusion performs online spatial and temporal sensor calibration between all three asynchronous sensors, in...

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