國立虎尾科技大學 |

UAV Path Planning and Multi-Modal Localization for Mapping in a Subterranean Environment.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	UAV Path Planning and Multi-Modal Localization for Mapping in a Subterranean Environment./
作者:	Samarakoon, Kieren Yoshiki.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:	69 p.
附註:	Source: Masters Abstracts International, Volume: 84-05.
Contained By:	Masters Abstracts International84-05.
標題:	Transportation. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29731035
ISBN:	9798352980552

UAV Path Planning and Multi-Modal Localization for Mapping in a Subterranean Environment.
Samarakoon, Kieren Yoshiki.

UAV Path Planning and Multi-Modal Localization for Mapping in a Subterranean Environment. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 69 p.

Source: Masters Abstracts International, Volume: 84-05.

Thesis (M.Sc.)--West Virginia University, 2022.

This item must not be sold to any third party vendors.

The use of Unmanned Aerial Vehicles (UAVs), especially quadcopters, have become popular in academia and industry due to their small size and maneuverability. These UAVs can be programmed to autonomously execute missions that are usually difficult and risky for humans, such as subterranean exploration, infrastructure surveying, and even disaster response. However, inaccessible and remote environments pose a challenge in terms of navigation as they often lack access to Global Navigation Satellite System (GNSS) connections and lack features. To address these challenges, UAVs are equipped with multiple sensors to acquire different types of data. These include range, acceleration, and even images, which are fused to estimate a localization solution. The Autonomous Robotic Early Warning System for Underground Stone Mining Safety project, sponsored by Alpha Foundation, is conducted within the Statler College at West Virginia University (WVU). The project aims to map walls and pillars within a mine to analyze its structural integrity and safety. This thesis investigates the implementation of a path planning strategy to optimize the coverage of a wall and also the use of an error state Extended Kalman Filter (EKF) for sensor fusion to perform Simultaneous Localization and Mapping (SLAM). The experiments were carried out both in simulated and real world environments. In these experiments, the UAV was equipped with an Inertial Measurement Unit (IMU), laser altimeter, Ultra-Wideband (UWB) module (for ranging data), LiDAR for mapping, and an RGB-D camera to provide a Visual Odometry (VO) solution. In the simulation, the 3D reconstruction and odometry was compared to the ground truth, whereas the real experiment provided further insight into the strategy’s feasibility.

ISBN: 9798352980552Subjects--Topical Terms:

558117
Transportation.

UAV Path Planning and Multi-Modal Localization for Mapping in a Subterranean Environment.
LDR:02964nam a2200373 4500 001 1104676
005 20230619080117.5
006 m o d
007 cr#unu||||||||
008 230907s2022 ||||||||||||||||| ||eng d
020 $a 9798352980552
035 $a (MiAaPQ)AAI29731035
035 $a (MiAaPQ)WVirginia12337
035 $a AAI29731035
040 $a MiAaPQ $c MiAaPQ
100 1 $a Samarakoon, Kieren Yoshiki. $3 1413641
245 1 0 $a UAV Path Planning and Multi-Modal Localization for Mapping in a Subterranean Environment.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2022
300 $a 69 p.
500 $a Source: Masters Abstracts International, Volume: 84-05.
500 $a Advisor: Gross, Jason N. ;Pereira, Guilherme A. S. ;Gu, Yu;Tulu, Ihsan Berk.
502 $a Thesis (M.Sc.)--West Virginia University, 2022.
506 $a This item must not be sold to any third party vendors.
520 $a The use of Unmanned Aerial Vehicles (UAVs), especially quadcopters, have become popular in academia and industry due to their small size and maneuverability. These UAVs can be programmed to autonomously execute missions that are usually difficult and risky for humans, such as subterranean exploration, infrastructure surveying, and even disaster response. However, inaccessible and remote environments pose a challenge in terms of navigation as they often lack access to Global Navigation Satellite System (GNSS) connections and lack features. To address these challenges, UAVs are equipped with multiple sensors to acquire different types of data. These include range, acceleration, and even images, which are fused to estimate a localization solution. The Autonomous Robotic Early Warning System for Underground Stone Mining Safety project, sponsored by Alpha Foundation, is conducted within the Statler College at West Virginia University (WVU). The project aims to map walls and pillars within a mine to analyze its structural integrity and safety. This thesis investigates the implementation of a path planning strategy to optimize the coverage of a wall and also the use of an error state Extended Kalman Filter (EKF) for sensor fusion to perform Simultaneous Localization and Mapping (SLAM). The experiments were carried out both in simulated and real world environments. In these experiments, the UAV was equipped with an Inertial Measurement Unit (IMU), laser altimeter, Ultra-Wideband (UWB) module (for ranging data), LiDAR for mapping, and an RGB-D camera to provide a Visual Odometry (VO) solution. In the simulation, the 3D reconstruction and odometry was compared to the ground truth, whereas the real experiment provided further insight into the strategy’s feasibility.
590 $a School code: 0256.
650 4 $a Transportation. $3 558117
650 4 $a Robotics. $3 561941
650 4 $a Public administration. $3 562473
650 4 $a Mining. $3 1413645
650 4 $a Aerospace engineering. $3 686400
650 4 $a Vehicles. $3 721652
650 4 $a Localization. $3 1091696
650 4 $a Unmanned aerial vehicles. $3 1372845
650 4 $a Emergency communications systems. $3 1413644
650 4 $a Mapping. $3 1215615
650 4 $a Robots. $3 654842
650 4 $a Maps. $3 889832
650 4 $a Sensors. $3 1003702
650 4 $a Planning. $3 660157
650 4 $a Emergency preparedness. $3 1413643
650 4 $a Cameras. $3 812890
650 4 $a Mines. $3 1413642
690 $a 0538
690 $a 0551
690 $a 0617
690 $a 0771
690 $a 0709
710 2 $a West Virginia University. $3 1187945
773 0 $t Masters Abstracts International $g 84-05.
790 $a 0256
791 $a M.Sc.
792 $a 2022
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29731035