Development and Flight Performance of the Autonomous Navigation Feature Catalog for OSIRIS-REx Asteroid Sample Collection

Courtney Mario, Curtis Miller, Chris Norman, Ryan Olds, Eric Palmer, John Weirich, David A. Lorenz, Olivier S. Barnouin, Michael G. Daly, Jeff A. Seabrook, Brent J. Bos, Bashar Rizk, Dante S. Lauretta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

– The OSIRIS-REx spacecraft successfully collected a sample from the asteroid Bennu in October 2020, enabled by the vision navigation system Natural Feature Tracking (NFT). NFT autonomously provided state updates by matching features defined from Bennu shape model data to onboard camera images and allowed the spacecraft to touch down within 1 meter of the targeted location. This paper presents the development process and flight performance of the feature catalog used for navigation, including findings about terrain characteristics of robust features, validation methodologies despite limited test imagery, and trends between feature terrain content and final feature performance.

Original languageEnglish (US)
Title of host publicationAIAA SciTech Forum 2022
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624106316
DOIs
StatePublished - 2022
Externally publishedYes
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 - San Diego, United States
Duration: Jan 3 2022Jan 7 2022

Publication series

NameAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
Country/TerritoryUnited States
CitySan Diego
Period1/3/221/7/22

ASJC Scopus subject areas

  • Aerospace Engineering

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