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04-Automazione e Robotica

Vision-based pose estimation of an unknown and uncooperative object for on-orbit servicing and debris removal applications

azienda Tesi esterna in azienda    


Parole chiave AUTONOMOUS NAVIGATION, EMBEDDED SYSTEMS, SATELLITE NAVIGATION, VISION

Riferimenti MARTINA MAMMARELLA

Riferimenti esterni Fabrizio Dabbene (CNR-IEIIT); Federica Paganelli (AIKO); Luca Romanelli (AIKO)

Gruppi di ricerca 04-Automazione e Robotica

Tipo tesi SPERIMENTAL AND MODELLING

Descrizione Nowadays all the major space agencies and industries are undertaking the enhancement of the automation capabilities of spacecraft. Autonomous operations are extremely advantageous for space missions, with a wide range of possible applications. For example, autonomous relative navigation around unknown and uncooperative objects is particularly appealing. Precise pose and motion estimation of an uncooperative object, such as a Resident Space Object (RSO) has a potential utilization in the domain of space debris removal and on-orbit servicing. This thesis aims to explore the potential of combining vision-based pose estimation with filtering methods. In today's context, vision-based systems offer a promising approach to achieve highly accurate relative trajectory estimation for satellites. By equipping satellites with cameras, we not only enhance their ability to investigate Resident Space Objects (RSOs) but also expand their sensor capabilities for autonomous navigation tasks. The initial pose estimate obtained from the camera, which includes information about the relative position and attitude between the observing satellite and the RSO, can be integrated into the navigation filter. This data can then be fused with signals from other sources such as GPS, Sun sensors, Star trackers, IMU, and more.
The candidate will be responsible for developing a navigation system that integrates information from the camera and the onboard sensors. The main objective is to address a specific use case involving a Low Earth Orbit RSO, which refers to debris that needs to be captured and guided toward a re-entry trajectory.
The project will involve a range of different activities, starting from modeling the sensors installed on board to designing a robust filtering technique for accurately estimating the pose of the RSO throughout its orbit.
The candidate will review and explore different filtering techniques, considering both classical and Artificial Intelligence approaches, and select the most suitable one based on the mission scenario, computational limitations, and robustness requirements.

Vedi anche  cnr+aiko - thesis proposal.pdf 

Conoscenze richieste  Estimation theory sensor fusion, computer vision, robotics
MATLAB/Simulink and Python coding skills; C++ preferred but not required
Spoken/written English (excellent)


Scadenza validita proposta 12/07/2024      PROPONI LA TUA CANDIDATURA




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