NDLI: Accurate fast-mapping Range-Only SLAM for UAS applications

Content Provider	IEEE Xplore Digital Library
Author	Torres-Gonzalez, A. Martinez-de Dios, J.R. Ollero, A.
Copyright Year	2015
Description	Author affiliation: Vision & Control Res. Group, Univ. of Seville, Seville, Spain (Torres-Gonzalez, A.; Martinez-de Dios, J.R.; Ollero, A.)
Abstract	This paper deals with 3D Range-Only (RO) Simultaneous Localization and Mapping (SLAM), where the UAS integrates range measurements to a number of beacons in the environment. In the recent years RO-SLAM has attracted significant interest, it is suitable for non line-of-sight conditions and/or bad lighting, being superior to visual SLAM in some problems. However, some issues constrain its applicability in practical cases, such as delays in map building and low map and UAS estimation accuracies. This paper proposes a 3D RO-SLAM scheme for UAS that specifically focuses on improving map building delays and accuracy levels without penalizing efficiency in the consumption of resources. The proposed scheme presents two main advantages: 1) it integrates inter-beacon measurements, which significantly reduces map building times and improves map and UAS localization accuracies; and 2) it is endowed with a supervisory module that self-adapts the measurements that are integrated in SLAM reducing resource consumption. Experimental validation in field experiments with an octorotor UAS showed that the proposed scheme improved map building times in 80%, map accuracy in 31% and UAS localization accuracy in 18%.
Starting Page	543
Ending Page	550
File Size	2500835
Page Count	8
File Format	PDF
e-ISBN	9781479960101
DOI	10.1109/ICUAS.2015.7152334
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Simultaneous localization and mapping Accuracy Three-dimensional displays Buildings Estimation
Content Type	Text
Resource Type	Article

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