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Lunar Crater Detection for a Space Manoeuvre Simulation Vehicle
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this Master’s thesis, algorithms for autonomous lunar crater detection for a satellite manoeuvre simulation vehicle (SMSV) has been investigated. The SMSV is driving on a zero gravity surface under an artificial moon surface. The vehicle has a camera attached on the top. That camera will be used for the detection of craters. There are a great amount of different approaches towards crater detection in miscellaneous articles. Such as, Hough circle transform, Canny edge detection, Ellipse fitting and the training of a cascade classifier by using Haar-like features. All the different approaches were implemented and compared, until a final version of the best algorithm was found. It was established, that the best way of detecting craters at an artificial moon surface, containing irregular shaped craters, is to train a cascade classifier using Haar-like features. This approach was also compared at different stages of the classifiers and different classifiers were also compared.

Place, publisher, year, edition, pages
2016.
Identifiers
URN: urn:nbn:se:ltu:diva-350OAI: oai:DiVA.org:ltu-350DiVA, id: diva2:974594
External cooperation
Educational program
Space Engineering, master's level
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Examiners
Available from: 2016-09-27 Created: 2016-09-27 Last updated: 2016-09-27Bibliographically approved

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CiteExportLink to record
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