Thesis
Artificial Intelligence-assisted optical navigation for small body missions with application to Hera
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2025
- Thesis identifier
- T17449
- Person Identifier (Local)
- 202188560
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- Planetary defence against asteroid is a booming field in the space sector. High-level of autonomy is required on board spacecraft during their proximity operations around these small bodies, both to cope with the highly uncertain non-linear dynamical environment which surrounds them, and to reduce ground operation complexity related to the significant delays in communication covering the distances involved in these missions. This thesis presents an Artificial Intelligence (AI)-assisted Image Processing (IP) algorithm to support the optical navigation of asteroid rendezvous missions during their close proximity operations. By focusing on the case scenario of the ESA’s Hera mission to binary asteroid system (65803) Didymos, this work aims to tackle challenges of the current paradigm of methodologies involved in standard and intelligent IP algorithms. Firstly, by exploiting Convolutional Neural Networks, the algorithm is designed and developed to cope with scenarios involving adverse illumination conditions, irregular shape of the target body and the presence of external bodies. Secondly, the algorithm is refined and implemented in an Open Loop navigation system to assess its performances in the context of proximity operations. Finally an incremental validation test campaign is performed to assess the applicability of the developed algorithm on board asteroid rendezvous missions spacecraft. The test campaign objective is twofold: on one hand it aims to solve standard AI-related issues, i.e. bridging domain gaps to account for contingencies; on the other it aims to validate the algorithm on board spaceborne computers within the Guidance, Navigation and Control system of the spacecraft. This thesis primarily contributes by designing and implementing a structured pipeline for deploying AI-based IP algorithm in asteroid optical navigation, enabling a systematic evaluation of its suitability and performance.
- Advisor / supervisor
- Feng, Jinglang
- Gil-Fernández, Jesús
- Resource Type
- DOI
Relations
Contenu
| La vignette | Titre | Date de téléchargement | Visibilité | actes |
|---|---|---|---|---|
|
|
PDF of thesis T17449 | 2025-09-16 | Public | Télécharger |