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An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping

Research output: Contribution to conference - Without ISBN/ISSN Abstractpeer-review

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An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping. / Gu, Xiaowei; Angelov, Plamen; Khan, Muhammad.

2019. Abstract from Workshops -2019 IEEE Nuclear Science Symposium and Medical Imaging Conference.

Research output: Contribution to conference - Without ISBN/ISSN Abstractpeer-review

Harvard

Gu, X, Angelov, P & Khan, M 2019, 'An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping', Workshops -2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, 26/10/19 - 2/11/19.

APA

Gu, X., Angelov, P., & Khan, M. (2019). An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping. Abstract from Workshops -2019 IEEE Nuclear Science Symposium and Medical Imaging Conference.

Vancouver

Gu X, Angelov P, Khan M. An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping. 2019. Abstract from Workshops -2019 IEEE Nuclear Science Symposium and Medical Imaging Conference.

Author

Gu, Xiaowei ; Angelov, Plamen ; Khan, Muhammad. / An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping. Abstract from Workshops -2019 IEEE Nuclear Science Symposium and Medical Imaging Conference.

Bibtex

@conference{f4ea783d11df42539882b658ddc861c1,
title = "An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping",
abstract = "Simultaneous localization and mapping (SLAM) in unknown GPS-denied environments is a very challenging problem due to the complex environment factors and the lack of prior knowledge of such environments. The performance of standard SLAM methods is dependent on odometer measurements, which, however, are unlikely to be reliable in a challenging operating environment. In this paper, a novel odometer-free approach is introduced for unmanned ground-based vehicle (UGV) to perform SLAM using only LIDAR/SONAR scans in the form of discrete point clouds. The proposed odometer-free SLAM (OF-SLAM) approach can precisely align successive sensor scans without involving other auxiliary information, e.g., odometer readings. By converting the accurately aligned point clouds into continuous local grid maps using kernel tricks, OF-SLAM creates a dynamically updating global map of the surrounding environment and further accurately localizes the UGV on the map. Simulation experiments verify the validity and effectiveness of OF-SLAM and demonstrate the proposed approach as an attractive alternative for UGV to perform SLAM and explore complex unknown environments.",
author = "Xiaowei Gu and Plamen Angelov and Muhammad Khan",
year = "2019",
month = oct,
day = "26",
language = "English",
note = " Workshops -2019 IEEE Nuclear Science Symposium and Medical Imaging Conference : WS5 Robotics and autonomous platforms in nuclear applications ; Conference date: 26-10-2019 Through 02-11-2019",
url = "https://nssmic.ieee.org/2019/workshops/",

}

RIS

TY - CONF

T1 - An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping

AU - Gu, Xiaowei

AU - Angelov, Plamen

AU - Khan, Muhammad

PY - 2019/10/26

Y1 - 2019/10/26

N2 - Simultaneous localization and mapping (SLAM) in unknown GPS-denied environments is a very challenging problem due to the complex environment factors and the lack of prior knowledge of such environments. The performance of standard SLAM methods is dependent on odometer measurements, which, however, are unlikely to be reliable in a challenging operating environment. In this paper, a novel odometer-free approach is introduced for unmanned ground-based vehicle (UGV) to perform SLAM using only LIDAR/SONAR scans in the form of discrete point clouds. The proposed odometer-free SLAM (OF-SLAM) approach can precisely align successive sensor scans without involving other auxiliary information, e.g., odometer readings. By converting the accurately aligned point clouds into continuous local grid maps using kernel tricks, OF-SLAM creates a dynamically updating global map of the surrounding environment and further accurately localizes the UGV on the map. Simulation experiments verify the validity and effectiveness of OF-SLAM and demonstrate the proposed approach as an attractive alternative for UGV to perform SLAM and explore complex unknown environments.

AB - Simultaneous localization and mapping (SLAM) in unknown GPS-denied environments is a very challenging problem due to the complex environment factors and the lack of prior knowledge of such environments. The performance of standard SLAM methods is dependent on odometer measurements, which, however, are unlikely to be reliable in a challenging operating environment. In this paper, a novel odometer-free approach is introduced for unmanned ground-based vehicle (UGV) to perform SLAM using only LIDAR/SONAR scans in the form of discrete point clouds. The proposed odometer-free SLAM (OF-SLAM) approach can precisely align successive sensor scans without involving other auxiliary information, e.g., odometer readings. By converting the accurately aligned point clouds into continuous local grid maps using kernel tricks, OF-SLAM creates a dynamically updating global map of the surrounding environment and further accurately localizes the UGV on the map. Simulation experiments verify the validity and effectiveness of OF-SLAM and demonstrate the proposed approach as an attractive alternative for UGV to perform SLAM and explore complex unknown environments.

M3 - Abstract

T2 - Workshops -2019 IEEE Nuclear Science Symposium and Medical Imaging Conference

Y2 - 26 October 2019 through 2 November 2019

ER -