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Machine learning techniques applied to images processing of small sats involved in interplanetary mission supporting the Martian rovers navigation

keywords IMAGE PROCESSING, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS, MARTIAN ROVERS, SMALL SATELLITES

Reference persons FABRIZIO STESINA

External reference persons Ing. Francesco Santoro (ALTEC)

Research Groups 22-Progetto e sviluppo di sistemi e tecnologie aerospaziali

Description The thesis aims to develop strategies and algorithms supporting navigation of a planetary rover on Mars making use of terrain images acquired by a drone at a height of 5-20 meters above the ground and a constellation of small satellites at 80-150 km. Objective is to identify obstacles and define specific traversability maps.
The thesis will take place according to the following points:
State-of-the-art analysis of machine and deep learning algorithms used for similar applications
Definition of the requirements according to a specific use case and the available datasets to be used for training and system testing
Development of algorithms possibly starting from existing open-source solutions and / or pre-trained algorithms
Verification of the solution by simulation and / or laboratory tests made using dedicated facilities
Note: the thesis will be developed within the SINAV project funded by the Italian Space Agency.

Required skills Space mission and system design
Basics on C/C++ and Phyton
Team working


Deadline 31/10/2022      PROPONI LA TUA CANDIDATURA




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