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Obstacle avoidance with optic flow

Thesis (MEng)--Stellenbosch University, 2019.

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Bibliographic Details
Main Author: Craeye, Cian Alexander
Other Authors: Smit, W. J.
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2019
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access_status_str Open Access
author Craeye, Cian Alexander
author2 Smit, W. J.
author_browse Craeye, Cian Alexander
Smit, W. J.
author_facet Smit, W. J.
Craeye, Cian Alexander
author_sort Craeye, Cian Alexander
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MEng)--Stellenbosch University, 2019.
format Thesis
id oai:scholar.sun.ac.za:10019.1/106146
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:43:40.048Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2019
publishDateRange 2019
publishDateSort 2019
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/106146 Obstacle avoidance with optic flow Craeye, Cian Alexander Smit, W. J. Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering (CRSES) FAST algorithm Lucas-Kanade pyramid algorithm Quadrotor helicopters -- Navigation Image processing -- Digital techniques UCTD Thesis (MEng)--Stellenbosch University, 2019. ENGLISH ABSTRACT: In order to determine the potential of using optical flow as an instrument for quadcopter navigation, a real-time depth estimation system was created. The system was programmed in Python and made use of: FAST algorithm to detect key points, Lucas-Kanade pyramid algorithm to calculate the optical flow, different geometrical relationships to calculate depth from translation and Euler angles to negate the effects of rotation. A simulated testing environment created in the Unity game engine was used to successfully test the overall performance, accuracy and robustness of the system. The positive results from the system and component tests proved that there is potential in using optical flow in quadcopter navigation. AFRIKAANSE OPSOMMING: Ten einde die potensiaal van optiese vloei as 'n instrument vir hommeltuig navigasie te bepaal, is 'n intydse diepte skattingstelsel geskep. Die stelsel is in Python geprogrammeer en maak gebruik van: FAST-algoritme om sleutelpunte te bepaal, Lucas-Kanade piramide algoritme om optiese vloei op te spoor, verskillende geometriese verhoudings om diepte van beweging te bereken en Euler-hoeke om die effekte van rotasie te negeer. 'n Gesimuleerde toetsomgewing wat in die Unity enjin geskep is, is gebruik om die algehele prestasie, akkuraatheid en robuustheid van die stelsel suksesvol te toets. Die positiewe resultate van die stelsel- en komponenttoetse het getoon dat daar potensiaal is in die gebruik van optiese vloei in hommeltuig navigasie. 2019-02-27T08:56:19Z 2019-04-17T08:30:59Z 2019-02-27T08:56:19Z 2019-04-17T08:30:59Z 2019-04 Thesis http://hdl.handle.net/10019.1/106146 en_ZA Stellenbosch University xii, 98 pages : illustrations application/pdf Stellenbosch : Stellenbosch University
spellingShingle FAST algorithm
Lucas-Kanade pyramid algorithm
Quadrotor helicopters -- Navigation
Image processing -- Digital techniques
UCTD
Craeye, Cian Alexander
Obstacle avoidance with optic flow
title Obstacle avoidance with optic flow
title_full Obstacle avoidance with optic flow
title_fullStr Obstacle avoidance with optic flow
title_full_unstemmed Obstacle avoidance with optic flow
title_short Obstacle avoidance with optic flow
title_sort obstacle avoidance with optic flow
topic FAST algorithm
Lucas-Kanade pyramid algorithm
Quadrotor helicopters -- Navigation
Image processing -- Digital techniques
UCTD
url http://hdl.handle.net/10019.1/106146
work_keys_str_mv AT craeyecianalexander obstacleavoidancewithopticflow