Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial Odometry

Owing to the nonlinearity in visual-inertial state estimation, sufficiently accurate initial states, especially the spatial and temporal parameters between IMU (Inertial Measurement Unit) and camera, should be provided to avoid divergence. Moreover, these parameters are required to be calibrated onl...

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Main Authors: Zheyu Feng, Jianwen Li, Lundong Zhang, Chen Chen
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/10/2273
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spelling doaj-c0c071b882af47ac88a7d02cc52e93722020-11-24T21:30:35ZengMDPI AGSensors1424-82202019-05-011910227310.3390/s19102273s19102273Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial OdometryZheyu Feng0Jianwen Li1Lundong Zhang2Chen Chen3Information Engineering University, Zhengzhou 450001, ChinaInformation Engineering University, Zhengzhou 450001, ChinaInformation Engineering University, Zhengzhou 450001, ChinaInformation Engineering University, Zhengzhou 450001, ChinaOwing to the nonlinearity in visual-inertial state estimation, sufficiently accurate initial states, especially the spatial and temporal parameters between IMU (Inertial Measurement Unit) and camera, should be provided to avoid divergence. Moreover, these parameters are required to be calibrated online since they are likely to vary once the mechanical configuration slightly changes. Recently, direct approaches have gained popularity for their better performance than feature-based approaches in little-texture or low-illumination environments, taking advantage of tracking pixels directly. Based on these considerations, we perform a direct version of monocular VIO (Visual-inertial Odometry), and propose a novel approach to initialize the spatial-temporal parameters and estimate them with all other variables of interest (IMU pose, point inverse depth, etc.). We highlight that our approach is able to perform robust and accurate initialization and online calibration for the spatial and temporal parameters without utilizing any prior information, and also achieves high-precision estimates even when large temporal offset occurs. The performance of the proposed approach was verified through the public UAV (Unmanned Aerial Vehicle) dataset.https://www.mdpi.com/1424-8220/19/10/2273visual-inertial odometrydirect approachonline calibrationspatial-temporal parameters
collection DOAJ
language English
format Article
sources DOAJ
author Zheyu Feng
Jianwen Li
Lundong Zhang
Chen Chen
spellingShingle Zheyu Feng
Jianwen Li
Lundong Zhang
Chen Chen
Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial Odometry
Sensors
visual-inertial odometry
direct approach
online calibration
spatial-temporal parameters
author_facet Zheyu Feng
Jianwen Li
Lundong Zhang
Chen Chen
author_sort Zheyu Feng
title Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial Odometry
title_short Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial Odometry
title_full Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial Odometry
title_fullStr Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial Odometry
title_full_unstemmed Online Spatial and Temporal Calibration for Monocular Direct Visual-Inertial Odometry
title_sort online spatial and temporal calibration for monocular direct visual-inertial odometry
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2019-05-01
description Owing to the nonlinearity in visual-inertial state estimation, sufficiently accurate initial states, especially the spatial and temporal parameters between IMU (Inertial Measurement Unit) and camera, should be provided to avoid divergence. Moreover, these parameters are required to be calibrated online since they are likely to vary once the mechanical configuration slightly changes. Recently, direct approaches have gained popularity for their better performance than feature-based approaches in little-texture or low-illumination environments, taking advantage of tracking pixels directly. Based on these considerations, we perform a direct version of monocular VIO (Visual-inertial Odometry), and propose a novel approach to initialize the spatial-temporal parameters and estimate them with all other variables of interest (IMU pose, point inverse depth, etc.). We highlight that our approach is able to perform robust and accurate initialization and online calibration for the spatial and temporal parameters without utilizing any prior information, and also achieves high-precision estimates even when large temporal offset occurs. The performance of the proposed approach was verified through the public UAV (Unmanned Aerial Vehicle) dataset.
topic visual-inertial odometry
direct approach
online calibration
spatial-temporal parameters
url https://www.mdpi.com/1424-8220/19/10/2273
work_keys_str_mv AT zheyufeng onlinespatialandtemporalcalibrationformonoculardirectvisualinertialodometry
AT jianwenli onlinespatialandtemporalcalibrationformonoculardirectvisualinertialodometry
AT lundongzhang onlinespatialandtemporalcalibrationformonoculardirectvisualinertialodometry
AT chenchen onlinespatialandtemporalcalibrationformonoculardirectvisualinertialodometry
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