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3D Shape Reconstruction of Small Bodies From Sparse Features

3D Shape Reconstruction of Small Bodies From Sparse Features

Authors :
Benjamin Jarvis
Issa A. D. Nesnas
David S. Bayard
Benjamin Morrell
Benjamin J. Hockman
Jacopo Villa
Daniel P. Lubey
Shyam Bhaskaran
Gary P. T. Choi
Saptarshi Bandopadhyay
Source :
IEEE Robotics and Automation Letters. 6:7089-7096
Publication Year :
2021
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2021.

Abstract

The autonomous approach of spacecraft to a small body (comet or asteroid) relies on using all available information at each phase of the approach. This letter presents new algorithms for global shape reconstructions from sparse tracked surface points. These methods leverage estimates from earlier phases, such as rotation pole, as well as a priori knowledge, such as a genus-0 body (i.e. without boundaries or topological holes). A mapping algorithm is proposed, which performs faithful reconstructions while enforcing genus-0 output through spherical parameterization. To estimate the shape of permanently shadowed regions of the body, a symmetry reconstruction method is added to the reconstruction algorithms. This method is shown to substantially increase the reconstruction accuracy but is subject to the symmetry of the body perpendicular to the rotation pole. The proposed mapping algorithm is compared to state-of-the-practice surface reconstruction algorithms, assessing their accuracy and ability to correctly generate genus-0 shape models for 2400 datasets and three small bodies. The proposed spherical parameterization algorithm performed consistently with the state-of-the-practice while being the only algorithm to always produce genus-0 shape models.

Details

ISSN :
23773774
Volume :
6
Database :
OpenAIRE
Journal :
IEEE Robotics and Automation Letters
Accession number :
edsair.doi...........66b83b0895033e4abbdb853bb4e9f0a2
Full Text :
https://doi.org/10.1109/lra.2021.3097273