A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV)
A Master of Science thesis in Mechatronics Engineering by Milad Roigari entitled, "A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV)," submitted in May 2015. Thesis advisor is Dr. Mohammad Abdel Kareem Rasheed Jaradat and thesis co-advisor Dr. Mamoun...
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| Format: | doctoralThesis |
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2015
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| Online Access: | http://hdl.handle.net/11073/7868 |
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| _version_ | 1864513441153155072 |
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| author | Roigari, Milad |
| author_facet | Roigari, Milad |
| author_role | author |
| dc.contributor.none.fl_str_mv | Jaradat, Mohammad Abdel-Hafez, Mamoun |
| dc.creator.none.fl_str_mv | Roigari, Milad |
| dc.date.none.fl_str_mv | 2015-09-07T05:10:55Z 2015-09-07T05:10:55Z 2015-05 |
| dc.format.none.fl_str_mv | application/pdf application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2015.37 http://hdl.handle.net/11073/7868 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | Navigation Extended Kalman Filter Monte Carlo Localization Input Output State Feedback Linearization Dynamic Feedback Linearization Kinect Depth Camera Wireless localization Navigation Autonomous vehicles |
| dc.title.none.fl_str_mv | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
| description | A Master of Science thesis in Mechatronics Engineering by Milad Roigari entitled, "A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV)," submitted in May 2015. Thesis advisor is Dr. Mohammad Abdel Kareem Rasheed Jaradat and thesis co-advisor Dr. Mamoun Abdel-Hafez. Soft and hard copy available. |
| format | doctoralThesis |
| id | aus_ba6cf6a5cee172dfd5ae2272ee31f352 |
| identifier_str_mv | 35.232-2015.37 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/7868 |
| publishDate | 2015 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV)Roigari, MiladNavigationExtended Kalman FilterMonte Carlo LocalizationInput Output State Feedback LinearizationDynamic Feedback LinearizationKinectDepth CameraWireless localizationNavigationAutonomous vehiclesA Master of Science thesis in Mechatronics Engineering by Milad Roigari entitled, "A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV)," submitted in May 2015. Thesis advisor is Dr. Mohammad Abdel Kareem Rasheed Jaradat and thesis co-advisor Dr. Mamoun Abdel-Hafez. Soft and hard copy available.This thesis presents an approach for solving the global navigation problem of wheeled mobile robots. The presented solution for outdoor navigation uses Extended Kalman Filter (EKF) to estimate the robot location based on the measurements from Global Positioning System (GPS), inertial measurement unit (IMU) and wheel encoders. For indoor navigation (where GPS signals are blocked) another probabilistic approach, based on Monte Carlo Localization (MCL), is used for localization. This algorithm utilizes the map of the environment to estimate the posterior of the robot using the depth measurements from a Kinect sensor. The output from the Kinect sensor is processed to imitate the output of a 2D laser scanner by projecting the points from a thin horizontal strip of pixels in the image plane to the corresponding real world 3D coordinates using the pin-hole camera model. Two different controllers based on Dynamic Feedback Linearization (DFL) and Input-Output State Feedback Linearization (I-O SFL) have been analyzed, simulated and compared. Based on the thesis objective and the simulated results, the I-O SFL method was chosen for solving the trajectory tracking problem. A set of test experiments was conducted to evaluate the performance of the proposed system in outdoor, indoor and a combination of both environments. The results show that the robot can successfully navigate through the way-points with a great accuracy in indoor environments, while the accuracy in outdoor environments is within the 3m position accuracy of the GPS.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR)Jaradat, MohammadAbdel-Hafez, Mamoun2015-09-07T05:10:55Z2015-09-07T05:10:55Z2015-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdf35.232-2015.37http://hdl.handle.net/11073/7868en_USoai:repository.aus.edu:11073/78682025-06-26T12:23:50Z |
| spellingShingle | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) Roigari, Milad Navigation Extended Kalman Filter Monte Carlo Localization Input Output State Feedback Linearization Dynamic Feedback Linearization Kinect Depth Camera Wireless localization Navigation Autonomous vehicles |
| status_str | publishedVersion |
| title | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) |
| title_full | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) |
| title_fullStr | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) |
| title_full_unstemmed | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) |
| title_short | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) |
| title_sort | A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV) |
| topic | Navigation Extended Kalman Filter Monte Carlo Localization Input Output State Feedback Linearization Dynamic Feedback Linearization Kinect Depth Camera Wireless localization Navigation Autonomous vehicles |
| url | http://hdl.handle.net/11073/7868 |