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Precision instrument targeting via image registration for the Mars 2020 Rover

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dc.contributor.author Doran, Gary
dc.contributor.author Thompson, David R.
dc.contributor.author Estlin, Tara
dc.date.accessioned 2019-05-16T17:00:27Z
dc.date.available 2019-05-16T17:00:27Z
dc.date.issued 2016-07-09
dc.identifier.citation International Joint Conference on Artificial Intelligence, New York City, New York, July 9-15, 2016 en_US
dc.identifier.clearanceno 16-1757
dc.identifier.uri http://hdl.handle.net/2014/46101
dc.description.abstract A key component of Mars exploration is the operation of robotic instruments on the surface, such as those on board the Mars Exploration Rovers, the Mars Science Laboratory (MSL), and the planned Mars 2020 Rover. As the instruments carried by these rovers have become more advanced, the area targeted by some instruments becomes smaller, revealing more fine-grained details about the geology and chemistry of rocks on the surface. However, thermal fluctuations, rover settling or slipping, and inherent inaccuracies in pointing mechanisms all lead to pointing error that is on the order of the target size (several millimeters) or larger. We show that given a target located on a previously acquired image, the rover can align this with a new image to visually locate the target and refine the current pointing. Due to round-trip communication constraints, this visual targeting must be done efficiently on board the rover using relatively limited computing hardware. We employ existing ORB features for landmark-based image registration, describe and theoretically justify a novel approach to filtering false landmark matches, and employ a random forest classifier to automatically reject failed alignments. We demonstrate the efficacy of our approach using over 3,800 images acquired by Remote Micro-Imager on board the “Curiosity” rover. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2016 en_US
dc.title Precision instrument targeting via image registration for the Mars 2020 Rover en_US
dc.type Preprint en_US


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