A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR

Sensor fusion based localization techniques often need accurate estimate of the fast and uncertain scene change in environment. To determine the scene change from two consecutive LIDAR scans, this paper proposes a novel technique called 'keep zero as zero' polar correlation. As it name i...

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Main Authors: SIDHARTHAN, R. K., KANNAN, R., SRINIVASAN, S., BALAS, M. M.
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2016-11-01
Series:Advances in Electrical and Computer Engineering
Subjects:
Online Access:http://dx.doi.org/10.4316/AECE.2016.04003
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spelling doaj-8c42762ce7bd4bab94255286c911a66c2020-11-25T01:06:11ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002016-11-01164152210.4316/AECE.2016.04003A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDARSIDHARTHAN, R. K.KANNAN, R.SRINIVASAN, S.BALAS, M. M.Sensor fusion based localization techniques often need accurate estimate of the fast and uncertain scene change in environment. To determine the scene change from two consecutive LIDAR scans, this paper proposes a novel technique called 'keep zero as zero' polar correlation. As it name implies any zero in the scan data is kept isolated from scene change estimation as it do not carry any information about scene change. Unlike existing techniques, the proposed methodology employs minimization of selective horizontal and vertically shifted sum of difference between the scans to estimate scene change in terms of rotation and translation. Minimization of the proposed correlation function across the specified search space can guarantee an accurate estimate of scene change without any ambiguity. The performance of the proposed method is tested experimentally on a mobile robot in two modes depending on the scene change. In the first mode, scene change is detected using dynamic LIDAR, whereas static LIDAR is used in the second mode. The proposed methodology is found to be more robust to environmental uncertainties with a reliable level of localization accuracy.http://dx.doi.org/10.4316/AECE.2016.04003correlationmobile robotspattern matchingsensor fusionsimultaneous localization and mapping
collection DOAJ
language English
format Article
sources DOAJ
author SIDHARTHAN, R. K.
KANNAN, R.
SRINIVASAN, S.
BALAS, M. M.
spellingShingle SIDHARTHAN, R. K.
KANNAN, R.
SRINIVASAN, S.
BALAS, M. M.
A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR
Advances in Electrical and Computer Engineering
correlation
mobile robots
pattern matching
sensor fusion
simultaneous localization and mapping
author_facet SIDHARTHAN, R. K.
KANNAN, R.
SRINIVASAN, S.
BALAS, M. M.
author_sort SIDHARTHAN, R. K.
title A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR
title_short A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR
title_full A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR
title_fullStr A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR
title_full_unstemmed A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR
title_sort novel keep zero as zero polar correlation technique for mobile robot localization using lidar
publisher Stefan cel Mare University of Suceava
series Advances in Electrical and Computer Engineering
issn 1582-7445
1844-7600
publishDate 2016-11-01
description Sensor fusion based localization techniques often need accurate estimate of the fast and uncertain scene change in environment. To determine the scene change from two consecutive LIDAR scans, this paper proposes a novel technique called 'keep zero as zero' polar correlation. As it name implies any zero in the scan data is kept isolated from scene change estimation as it do not carry any information about scene change. Unlike existing techniques, the proposed methodology employs minimization of selective horizontal and vertically shifted sum of difference between the scans to estimate scene change in terms of rotation and translation. Minimization of the proposed correlation function across the specified search space can guarantee an accurate estimate of scene change without any ambiguity. The performance of the proposed method is tested experimentally on a mobile robot in two modes depending on the scene change. In the first mode, scene change is detected using dynamic LIDAR, whereas static LIDAR is used in the second mode. The proposed methodology is found to be more robust to environmental uncertainties with a reliable level of localization accuracy.
topic correlation
mobile robots
pattern matching
sensor fusion
simultaneous localization and mapping
url http://dx.doi.org/10.4316/AECE.2016.04003
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