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You searched for +publisher:"University of New South Wales" +contributor:("Garratt, Matthew, Engineering & Information Technology, UNSW Canberra, UNSW"). Showing records 1 – 5 of 5 total matches.

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University of New South Wales

1. Wang, Jiefei. Control of Low Speed Flight in Cluttered Environments Using Image Motion and Ranging on a Micro-Air Vehicle.

Degree: Engineering & Information Technology, 2016, University of New South Wales

 This thesis focuses on the issue of real-time low speed flight of Micro-Air-Vehicles(MAVs) in cluttered environments. In order to achieve real-time autonomous operation,we have developed… (more)

Subjects/Keywords: Optical Flow; Micro Aerial Vehicle; Autonomous Ground Vehicle; Binary Image; Ego-motion Recovery; Sensor Fusion; Path Planning; Dense Scene Flow

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APA (6th Edition):

Wang, J. (2016). Control of Low Speed Flight in Cluttered Environments Using Image Motion and Ranging on a Micro-Air Vehicle. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/56875 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41824/SOURCE01?view=true

Chicago Manual of Style (16th Edition):

Wang, Jiefei. “Control of Low Speed Flight in Cluttered Environments Using Image Motion and Ranging on a Micro-Air Vehicle.” 2016. Doctoral Dissertation, University of New South Wales. Accessed October 17, 2019. http://handle.unsw.edu.au/1959.4/56875 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41824/SOURCE01?view=true.

MLA Handbook (7th Edition):

Wang, Jiefei. “Control of Low Speed Flight in Cluttered Environments Using Image Motion and Ranging on a Micro-Air Vehicle.” 2016. Web. 17 Oct 2019.

Vancouver:

Wang J. Control of Low Speed Flight in Cluttered Environments Using Image Motion and Ranging on a Micro-Air Vehicle. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2019 Oct 17]. Available from: http://handle.unsw.edu.au/1959.4/56875 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41824/SOURCE01?view=true.

Council of Science Editors:

Wang J. Control of Low Speed Flight in Cluttered Environments Using Image Motion and Ranging on a Micro-Air Vehicle. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/56875 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41824/SOURCE01?view=true


University of New South Wales

2. Habibi Tehrani, Mohsen. Aircraft Attitude Estimation Using Panoramic Images.

Degree: Engineering & Information Technology Canberra, 2014, University of New South Wales

 This thesis investigates the problem of reliably estimating attitude from panoramic imagery in cluttered environments. Accurate attitude is an essential input to the stabilisation systems… (more)

Subjects/Keywords: Aircraft Attitude Estimation; Panoramic Images; Estimating attitude; Cluttered environments; Ocelli organ; Real–; time horizon-based attitude estimation; Panoramic sky/ground thresholding; Three–; dimensional mapping; Image interpolation algorithm (I2A); Extended Kalman Filter (EKF); Artificial Neural Networks (ANNs); Flight tests

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APA (6th Edition):

Habibi Tehrani, M. (2014). Aircraft Attitude Estimation Using Panoramic Images. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/54009 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12717/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Habibi Tehrani, Mohsen. “Aircraft Attitude Estimation Using Panoramic Images.” 2014. Doctoral Dissertation, University of New South Wales. Accessed October 17, 2019. http://handle.unsw.edu.au/1959.4/54009 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12717/SOURCE02?view=true.

MLA Handbook (7th Edition):

Habibi Tehrani, Mohsen. “Aircraft Attitude Estimation Using Panoramic Images.” 2014. Web. 17 Oct 2019.

Vancouver:

Habibi Tehrani M. Aircraft Attitude Estimation Using Panoramic Images. [Internet] [Doctoral dissertation]. University of New South Wales; 2014. [cited 2019 Oct 17]. Available from: http://handle.unsw.edu.au/1959.4/54009 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12717/SOURCE02?view=true.

Council of Science Editors:

Habibi Tehrani M. Aircraft Attitude Estimation Using Panoramic Images. [Doctoral Dissertation]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/54009 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12717/SOURCE02?view=true


University of New South Wales

3. Li, Ping. Robust Sensing and Control of Micro Aerial Vehicles using a Monocular Camera and an Inertial Measurement Unit.

Degree: Engineering & Information Technology, 2016, University of New South Wales

 This thesis is concerned with the motion estimation and control of Micro Aerial Vehicles (MAVs) using a monocular camera and Inertial Measurement Unit (IMU). The… (more)

Subjects/Keywords: Optic Flow; Micro Aerial Vehicle; Visual Inertial Fusion; Illumination Variation; Monocular Sensing and Control; Snapshot

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APA (6th Edition):

Li, P. (2016). Robust Sensing and Control of Micro Aerial Vehicles using a Monocular Camera and an Inertial Measurement Unit. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/55898 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39626/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Li, Ping. “Robust Sensing and Control of Micro Aerial Vehicles using a Monocular Camera and an Inertial Measurement Unit.” 2016. Doctoral Dissertation, University of New South Wales. Accessed October 17, 2019. http://handle.unsw.edu.au/1959.4/55898 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39626/SOURCE02?view=true.

MLA Handbook (7th Edition):

Li, Ping. “Robust Sensing and Control of Micro Aerial Vehicles using a Monocular Camera and an Inertial Measurement Unit.” 2016. Web. 17 Oct 2019.

Vancouver:

Li P. Robust Sensing and Control of Micro Aerial Vehicles using a Monocular Camera and an Inertial Measurement Unit. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2019 Oct 17]. Available from: http://handle.unsw.edu.au/1959.4/55898 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39626/SOURCE02?view=true.

Council of Science Editors:

Li P. Robust Sensing and Control of Micro Aerial Vehicles using a Monocular Camera and an Inertial Measurement Unit. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/55898 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:39626/SOURCE02?view=true


University of New South Wales

4. Taylor, James. Optic Flow for Obstacle Avoidance and Navigation: A Practical Approach.

Degree: Engineering & Information Technology, 2016, University of New South Wales

 This thesis offers contributions and innovations to the development of vision-based autonomous flight control systems for small unmanned aerial vehicles operating in cluttered urban environments.… (more)

Subjects/Keywords: optic flow; Unmanned Aerial Vehicle; mini-UAV; navigation; obstacle avoidance; reactive control; terrain mapping

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APA (6th Edition):

Taylor, J. (2016). Optic Flow for Obstacle Avoidance and Navigation: A Practical Approach. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/56706 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41214/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Taylor, James. “Optic Flow for Obstacle Avoidance and Navigation: A Practical Approach.” 2016. Doctoral Dissertation, University of New South Wales. Accessed October 17, 2019. http://handle.unsw.edu.au/1959.4/56706 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41214/SOURCE02?view=true.

MLA Handbook (7th Edition):

Taylor, James. “Optic Flow for Obstacle Avoidance and Navigation: A Practical Approach.” 2016. Web. 17 Oct 2019.

Vancouver:

Taylor J. Optic Flow for Obstacle Avoidance and Navigation: A Practical Approach. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2019 Oct 17]. Available from: http://handle.unsw.edu.au/1959.4/56706 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41214/SOURCE02?view=true.

Council of Science Editors:

Taylor J. Optic Flow for Obstacle Avoidance and Navigation: A Practical Approach. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/56706 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41214/SOURCE02?view=true


University of New South Wales

5. Lin, Shanggang. Vision Based Shipboard Recovery of Unmanned Rotorcraft.

Degree: Engineering & Information Technology, 2017, University of New South Wales

 Landing an Unmanned Aerial Vehicle (UAV) autonomously and safely on a ship's flight deck is a challenging task for robotic researchers. The difficulties include large… (more)

Subjects/Keywords: Shipboard Landing; Unmanned Aerial Vehicle; Autonomous; Machine Vision; Target Recognition; Pose Estimation; Multi-Sensor Data Fusion; Ship Motion Prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lin, S. (2017). Vision Based Shipboard Recovery of Unmanned Rotorcraft. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/57597 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:44163/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Lin, Shanggang. “Vision Based Shipboard Recovery of Unmanned Rotorcraft.” 2017. Doctoral Dissertation, University of New South Wales. Accessed October 17, 2019. http://handle.unsw.edu.au/1959.4/57597 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:44163/SOURCE02?view=true.

MLA Handbook (7th Edition):

Lin, Shanggang. “Vision Based Shipboard Recovery of Unmanned Rotorcraft.” 2017. Web. 17 Oct 2019.

Vancouver:

Lin S. Vision Based Shipboard Recovery of Unmanned Rotorcraft. [Internet] [Doctoral dissertation]. University of New South Wales; 2017. [cited 2019 Oct 17]. Available from: http://handle.unsw.edu.au/1959.4/57597 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:44163/SOURCE02?view=true.

Council of Science Editors:

Lin S. Vision Based Shipboard Recovery of Unmanned Rotorcraft. [Doctoral Dissertation]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/57597 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:44163/SOURCE02?view=true

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