Next Article in Journal
Bioenergetic Health Assessment of a Single Caenorhabditis elegans from Postembryonic Development to Aging Stages via Monitoring Changes in the Oxygen Consumption Rate within a Microfluidic Device
Next Article in Special Issue
Design of a Multiband Global Navigation Satellite System Radio Frequency Interference Monitoring Front-End with Synchronized Secondary Sensors
Previous Article in Journal
Interaction of Lamb Wave Modes with Weak Material Nonlinearity: Generation of Symmetric Zero-Frequency Mode
Previous Article in Special Issue
Integrity and Collaboration in Dynamic Sensor Networks
Open AccessArticle

Accurate Collaborative Globally-Referenced Digital Mapping with Standard GNSS

1
Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA
2
Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX 78712, USA
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(8), 2452; https://doi.org/10.3390/s18082452
Received: 16 June 2018 / Revised: 25 July 2018 / Accepted: 26 July 2018 / Published: 28 July 2018
(This article belongs to the Special Issue GNSS and Fusion with Other Sensors)
Exchange of location and sensor data among connected and automated vehicles will demand accurate global referencing of the digital maps currently being developed to aid positioning for automated driving. This paper explores the limit of such maps’ globally-referenced position accuracy when the mapping agents are equipped with low-cost Global Navigation Satellite System (GNSS) receivers performing standard code-phase-based navigation, and presents a globally-referenced electro-optical simultaneous localization and mapping pipeline, called GEOSLAM, designed to achieve this limit. The key accuracy-limiting factor is shown to be the asymptotic average of the error sources that impair standard GNSS positioning. Asymptotic statistics of each GNSS error source are analyzed through both simulation and empirical data to show that sub-50-cm accurate digital mapping is feasible in the horizontal plane after multiple mapping sessions with standard GNSS, but larger biases persist in the vertical direction. GEOSLAM achieves this accuracy by (i) incorporating standard GNSS position estimates in the visual SLAM framework, (ii) merging digital maps from multiple mapping sessions, and (iii) jointly optimizing structure and motion with respect to time-separated GNSS measurements. View Full-Text
Keywords: vehicle localization; SLAM; sensor fusion vehicle localization; SLAM; sensor fusion
Show Figures

Figure 1

MDPI and ACS Style

Narula, L.; Wooten, J.M.; Murrian, M.J.; LaChapelle, D.M.; Humphreys, T.E. Accurate Collaborative Globally-Referenced Digital Mapping with Standard GNSS. Sensors 2018, 18, 2452.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop