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Development of Autonomous Bounding Box Algorithms for OPIC’s Data Prioritization on the Comet Interceptor Mission

The joint European Space Agency and Japan Aerospace Exploration Agency mission Comet Interceptor seeks to perform a flyby of a Small Solar System Body (SSSB), through use of a multi-element spacecraft. It comprises a primary spacecraft and two subspacecraft, the latter of which will encounter the intercepted object at a small enough distance that its end-of-life might occur at an impact of either the object itself or its potential coma. The Optical Periscopic Imager for Comets (OPIC) is an instrument implemented on one of these small probes which will generate monochromatic images during the encounter. Given a limited data budget before the possible impact, there is a need for data prioritization to ensure that only the most scientifically relevant data is collected. To enable this, algorithms for autonomously cropping an object nucleus from an image were developed during this thesis work. As the computational capabilities of OPIC are limited, the algorithms were required to be of low computational complexity. Additionally, given that the close environment of SSSB in general and comets in particular often exhibit considerable quantities of gas and dust which can generate cluttering in images, the algorithms developed were required to be resistant to noise. Three image cropping algorithms were developed with varying computational complexities. These were tested for cropping accuracy and relative execution times on data from both previous space missions as well as simulated photorealistic images. All three algorithms were able to properly find a bounding box of an object nucleus and any of its significant plumes. The accuracy in cropping correctness of the region borders generated increased with the computational complexity of the algorithms.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-89697
Date January 2022
CreatorsBrune, Eric
PublisherLuleå tekniska universitet, Rymdteknik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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