Lidar inertial odometry localization of UAV in indoor environment
Mobile robots are capable of various applications, ranging from simple delivery tasks to advanced surveillance operations. These abilities rely heavily on its localization ability, which provides stable and accurate pose estimations within the environment. Localization can be achieved by different...
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sg-ntu-dr.10356-776202023-03-04T18:36:32Z Lidar inertial odometry localization of UAV in indoor environment Chow, Jiun Fatt Seet Gim Lee, Gerald School of Mechanical and Aerospace Engineering Robotics Research Centre DRNTU::Engineering::Mechanical engineering Mobile robots are capable of various applications, ranging from simple delivery tasks to advanced surveillance operations. These abilities rely heavily on its localization ability, which provides stable and accurate pose estimations within the environment. Localization can be achieved by different sensors and techniques such as GPS, WIFI, ultrasonic sensors. In this paper, we focus on the laser-based localization method of UAV (drone) in a GPS-denied environment such as deep tunnel system. Due to the limited payload for sensors on a UAV, a 2D LIDAR sensor is used to perform 2D localization with the fusion of inertial measurement unit (IMU). IMU is an additional sensing input from the onboard flight control unit – Pixhawk, to increase the reliability and accuracy of localization performance. In this paper, we present a comparative analysis of the three most common laser-based 2D Simultaneous Localization and Mapping (SLAM) approached: Hector SLAM, Gmapping, Cartographer, in terms of localization against the precise ground truth and mapping quality. To evaluate the performance, experimental datasets were collected under the same conditions and compared to ground truth value in Motion Capture Lab. The experimental results were analysed in the aspect of accuracy and mapping quality via MATLAB. This study investigates these open-source packages and the real-time evaluations on the SLAM performance (i.e. localization and mapping) in surrounded environments. Bachelor of Engineering (Mechanical Engineering) 2019-06-03T07:02:48Z 2019-06-03T07:02:48Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77620 en Nanyang Technological University 78 p. application/pdf |
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DRNTU::Engineering::Mechanical engineering Chow, Jiun Fatt Lidar inertial odometry localization of UAV in indoor environment |
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Mobile robots are capable of various applications, ranging from simple delivery tasks to advanced surveillance operations. These abilities rely heavily on its localization ability, which provides stable and accurate pose estimations within the environment.
Localization can be achieved by different sensors and techniques such as GPS, WIFI, ultrasonic sensors. In this paper, we focus on the laser-based localization method of UAV (drone) in a GPS-denied environment such as deep tunnel system. Due to the limited payload for sensors on a UAV, a 2D LIDAR sensor is used to perform 2D localization with the fusion of inertial measurement unit (IMU).
IMU is an additional sensing input from the onboard flight control unit – Pixhawk, to increase the reliability and accuracy of localization performance. In this paper, we present a comparative analysis of the three most common laser-based 2D Simultaneous Localization and Mapping (SLAM) approached: Hector SLAM, Gmapping, Cartographer, in terms of localization against the precise ground truth and mapping quality.
To evaluate the performance, experimental datasets were collected under the same conditions and compared to ground truth value in Motion Capture Lab. The experimental results were analysed in the aspect of accuracy and mapping quality via MATLAB. This study investigates these open-source packages and the real-time evaluations on the SLAM performance (i.e. localization and mapping) in surrounded environments. |
author2 |
Seet Gim Lee, Gerald |
author_facet |
Seet Gim Lee, Gerald Chow, Jiun Fatt |
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Final Year Project |
author |
Chow, Jiun Fatt |
author_sort |
Chow, Jiun Fatt |
title |
Lidar inertial odometry localization of UAV in indoor environment |
title_short |
Lidar inertial odometry localization of UAV in indoor environment |
title_full |
Lidar inertial odometry localization of UAV in indoor environment |
title_fullStr |
Lidar inertial odometry localization of UAV in indoor environment |
title_full_unstemmed |
Lidar inertial odometry localization of UAV in indoor environment |
title_sort |
lidar inertial odometry localization of uav in indoor environment |
publishDate |
2019 |
url |
http://hdl.handle.net/10356/77620 |
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1759853765544902656 |