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Sensors 2016, 16(8), 1315;

Accurate Mobile Urban Mapping via Digital Map-Based SLAM

Robotics Program, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
This paper is an expanded version of Jeong, J.; Kim, A. Adaptive Inverse Perspective Mapping for Lane Map Generation with SLAM. In Proceedings of the IEEE Ubiquitous Robots and Ambient Intelligence, Xi’an, China, 19–22 August 2016.
Author to whom correspondence should be addressed.
Academic Editor: Dale A. Quattrochi
Received: 7 June 2016 / Revised: 5 August 2016 / Accepted: 11 August 2016 / Published: 18 August 2016
(This article belongs to the Section Remote Sensors)
Full-Text   |   PDF [22500 KB, uploaded 18 August 2016]   |  


This paper presents accurate urban map generation using digital map-based Simultaneous Localization and Mapping (SLAM). Throughout this work, our main objective is generating a 3D and lane map aiming for sub-meter accuracy. In conventional mapping approaches, achieving extremely high accuracy was performed by either (i) exploiting costly airborne sensors or (ii) surveying with a static mapping system in a stationary platform. Mobile scanning systems recently have gathered popularity but are mostly limited by the availability of the Global Positioning System (GPS). We focus on the fact that the availability of GPS and urban structures are both sporadic but complementary. By modeling both GPS and digital map data as measurements and integrating them with other sensor measurements, we leverage SLAM for an accurate mobile mapping system. Our proposed algorithm generates an efficient graph SLAM and achieves a framework running in real-time and targeting sub-meter accuracy with a mobile platform. Integrated with the SLAM framework, we implement a motion-adaptive model for the Inverse Perspective Mapping (IPM). Using motion estimation derived from SLAM, the experimental results show that the proposed approaches provide stable bird’s-eye view images, even with significant motion during the drive. Our real-time map generation framework is validated via a long-distance urban test and evaluated at randomly sampled points using Real-Time Kinematic (RTK)-GPS. View Full-Text
Keywords: 3D mapping; SLAM; digital map; urban mapping system; IPM; lane map 3D mapping; SLAM; digital map; urban mapping system; IPM; lane map

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

  • Externally hosted supplementary file 1
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    Description: A part of the material related to IPM (Fig8 and Fig9 in the manuscript) has been submitted for another conference, IEEE URAI( The conference is on Aug, and thus not published yet. We have completed proper copyright transfer with the conference.

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Roh, H.; Jeong, J.; Cho, Y.; Kim, A. Accurate Mobile Urban Mapping via Digital Map-Based SLAM
. Sensors 2016, 16, 1315.

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