Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Sejong Heo"'
Publikováno v:
Transaction of the Korean Society of Automotive Engineers. 30:839-847
Publikováno v:
IFAC-PapersOnLine. 55:40-45
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 69:7530-7541
In this article, we present self-calibrated visual–inertial odometry (VIO) that estimates inertial measurement unit (IMU) intrinsic parameters (scale factor and misalignment) using a stereo camera without any calibration boards. Most of the visual
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 20:2470-2479
In this paper, we present a hybrid visual inertial navigation algorithm for an autonomous and intelligent vehicle that combines the multi-state constraint Kalman filter (MSCKF) with the nonlinear visual-inertial graph optimization. The MSCKF is a wel
Publikováno v:
International Journal of Control, Automation and Systems. 17:743-751
In this paper, we present a patch-based direct visual odometry (DVO) that is robust to illumination changes at a sequence of stereo images. Illumination change violates the photo-consistency assumption and degrades the performance of DVO, thus, it sh
Publikováno v:
IEEE Sensors Journal. 18:7638-7649
In this paper, we present a novel visual-inertial navigation system (VINS) algorithm using points and lines for low cost and computationally constrained systems in GPS-denied environments. Generally, extended Kalman filter (EKF)-based VINS algorithms
Autor:
Sejong Heo, Chan Gook Park
Publikováno v:
IEEE Sensors Journal. 18:3780-3788
In this paper, we present a novel visual-inertial navigation algorithm for low-cost and computationally constrained vehicle in global positioning system denied environments by modeling the state space as the matrix Lie group (LG), based on the recent
Publikováno v:
Journal of the Korean Society for Aeronautical & Space Sciences. 45:836-843
Publikováno v:
IFAC-PapersOnLine. 50:2217-2222
In this paper, we present a robust multi-state constraint Kalman filter (MSCKF) for visual inertial navigation of mobile robots. We assume the hardware of a mobile robot consists of an inertial measurement unit (IMU) and a monocular camera. The MSCKF
Publikováno v:
E3S Web of Conferences, Vol 94, p 02005 (2019)
In this paper, we present a visual-inertial odometry (VIO) with an online calibration using a stereo camera in planetary rover localization. We augment the state vector with extrinsic (rigid body transformation) and temporal (time-offset) parameters