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Sensors 2019, 19(7), 1742; https://doi.org/10.3390/s19071742

An Orthogonal Weighted Occupancy Likelihood Map with IMU-Aided Laser Scan Matching for 2D Indoor Mapping

1
GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
2
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Received: 12 March 2019 / Revised: 8 April 2019 / Accepted: 9 April 2019 / Published: 11 April 2019
(This article belongs to the Section Remote Sensors)
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Abstract

An indoor map is a piece of infrastructure associated with location-based services. Simultaneous Localization and Mapping (SLAM)-based mobile mapping is an efficient method to construct an indoor map. This paper proposes an SLAM algorithm based on a laser scanner and an Inertial Measurement Unit (IMU) for 2D indoor mapping. A grid-based occupancy likelihood map is chosen as the map representation method and is built from all previous scans. Scan-to-map matching is utilized to find the optimal rigid-body transformation in order to avoid the accumulation of matching errors. Map generation and update are probabilistically motivated. According to the assumption that the orthogonal is the main feature of indoor environments, we propose a lightweight segment extraction method, based on the orthogonal blurred segments (OBS) method. Instead of calculating the parameters of segments, we give the scan points contained in blurred segments a greater weight during the construction of the grid-based occupancy likelihood map, which we call the orthogonal feature weighted occupancy likelihood map (OWOLM). The OWOLM enhances the occupancy likelihood map by fusing the orthogonal features. It can filter out noise scan points, produced by objects, such as glass cabinets and bookcases. Experiments were carried out in a library, which is a representative indoor environment, consisting of orthogonal features. The experimental result proves that, compared with the general occupancy likelihood map, the OWOLM can effectively reduce accumulated errors and construct a clearer indoor map. View Full-Text
Keywords: SLAM; orthogonal weighted occupancy likelihood map; IMU-aided laser scan matching; 2D indoor mapping SLAM; orthogonal weighted occupancy likelihood map; IMU-aided laser scan matching; 2D indoor mapping
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Qian, C.; Zhang, H.; Tang, J.; Li, B.; Liu, H. An Orthogonal Weighted Occupancy Likelihood Map with IMU-Aided Laser Scan Matching for 2D Indoor Mapping. Sensors 2019, 19, 1742.

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