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CORTO: The Celestial Object Rendering TOol at DART Lab

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The Celestial Object Rendering TOol (CORTO) offers a powerful solution for generating synthetic images of celestial bodies, catering to the needs of space mission design, algorithm development, and validation. Through rendering, noise modeling, hardware-in-the-loop testing, and post-processing functionalities, CORTO creates realistic scenarios. It offers a versatile and comprehensive solution for generating synthetic images of celestial bodies, aiding the development and validation of image processing and navigation algorithms for space missions. This work illustrates its functionalities in detail for the first time. The importance of a robust validation pipeline to test the tool’s accuracy against real mission images using metrics like normalized cross-correlation and structural similarity is also illustrated. CORTO is a valuable asset for advancing space exploration and navigation algorithm development and has already proven effective in various projects, including CubeSat design, lunar missions, and deep learning applications. While the tool currently covers a range of celestial body simulations, mainly focused on minor bodies and the Moon, future enhancements could broaden its capabilities to encompass additional planetary phenomena and environments.
Title: CORTO: The Celestial Object Rendering TOol at DART Lab
Description:
The Celestial Object Rendering TOol (CORTO) offers a powerful solution for generating synthetic images of celestial bodies, catering to the needs of space mission design, algorithm development, and validation.
Through rendering, noise modeling, hardware-in-the-loop testing, and post-processing functionalities, CORTO creates realistic scenarios.
It offers a versatile and comprehensive solution for generating synthetic images of celestial bodies, aiding the development and validation of image processing and navigation algorithms for space missions.
This work illustrates its functionalities in detail for the first time.
The importance of a robust validation pipeline to test the tool’s accuracy against real mission images using metrics like normalized cross-correlation and structural similarity is also illustrated.
CORTO is a valuable asset for advancing space exploration and navigation algorithm development and has already proven effective in various projects, including CubeSat design, lunar missions, and deep learning applications.
While the tool currently covers a range of celestial body simulations, mainly focused on minor bodies and the Moon, future enhancements could broaden its capabilities to encompass additional planetary phenomena and environments.

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