JPL Technical Report Server

Autonomous onboard science data analysis for comet missions

Show simple item record Thompson, David R. Tran, Daniel Q. McLaren, David Chien, Steve A. Bergman, Larry Castaño, Rebecca Doyle, Richard Estlin, Tara Lenda, Matthew 2012-10-26T20:33:40Z 2012-10-26T20:33:40Z 2012-09-04
dc.identifier.citation International Symposium on Artificial Intelligence Robotics and Automation in Space, Turnin, Italy, September 4-6, 2012 en_US
dc.identifier.clearanceno 12-2433
dc.description.abstract Coming years will bring several comet rendezvous missions. The Rosetta spacecraft arrives at Comet 67P/Churyumov–Gerasimenko in 2014. Subsequent rendezvous might include a mission such as the proposed Comet Hopper with multiple surface landings, as well as Comet Nucleus Sample Return (CNSR) and Coma Rendezvous and Sample Return (CRSR). These encounters will begin to shed light on a population that, despite several previous flybys, remains mysterious and poorly understood. Scientists still have little direct knowledge of interactions between the nucleus and coma, their variation across different comets or their evolution over time. Activity may change on short timescales so it is challenging to characterize with scripted data acquisition. Here we investigate automatic onboard image analysis that could act faster than round-trip light time to capture unexpected outbursts and plume activity. We describe one edge-based method for detect comet nuclei and plumes, and test the approach on an existing catalog of comet images. Finally, we quantify benefits to specific measurement objectives by simulating a basic plume monitoring campaign. 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, 2012. en_US
dc.subject comets en_US
dc.subject plume detection en_US
dc.subject computer vision en_US
dc.title Autonomous onboard science data analysis for comet missions en_US
dc.type Preprint en_US

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