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Identification of cryovolcanism on Titan using fuzzy cognitive maps

Furfaro, Roberto and Kargel, Jeffrey S. and Lunine, Jonathan I. and Fink, Wolfgang and Bishop, Michael P. (2010) Identification of cryovolcanism on Titan using fuzzy cognitive maps. Planetary and Space Science, 58 (5). pp. 761-779. ISSN 0032-0633.

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Future planetary exploration of Titan will require higher degrees of on-board automation, including autonomous determination of sites where the probability of significant scientific findings is the highest. In this paper, a novel Artificial Intelligence (AI) method for the identification and interpretation of sites that yield the highest potential of cryovolcanic activity is presented. We introduce the theory of fuzzy cognitive maps (FCM) as a tool for the analysis of remotely collected data in planetary exploration. A cognitive model embedded in a fuzzy logic framework is constructed via the synergistic interaction of planetary scientists and AI experts. As an application example, we show how FCM can be employed to solve the challenging problem of recognizing cryovolcanism from Synthetic Aperture Radar (SAR) Cassini data. The fuzzy cognitive map is constructed using what is currently known about cryovolcanism on Titan and relies on geological mapping performed by planetary scientists to interpret different locales as cryovolcanic in nature. The system is not conceived to replace the human scientific interpretation, but to enhance the scientists’ ability to deal with large amounts of data, and it is a first step in designing AI systems that will be able, in the future, to autonomously make decisions in situations where human analysis and interpretation is not readily available or could not be sufficiently timely. The proposed FCM is tested on Cassini radar data to show the effectiveness of the system in reaching conclusions put forward by human experts and published in the literature. Four tests are performed using the Ta SAR image (October 2004 fly-by). Two regions (i.e. Ganesa Macula and the lobate high backscattering region East of Ganesa) are interpreted by the designed FCM as exhibiting cryovolcanism in agreement with the initial interpretation of the regions by Stofan et al. (2006). Importantly, the proposed FCM is shown to be flexible and adaptive as new data and knowledge are acquired during the course of exploration. Subsequently, the FCM has been modified to include topographic information derived from SAR stereo data. With this additional information, the map concludes that Ganesa Macula is not a cryovolcanic region. In conclusion, the FCM methodology is shown to be a critical and powerful component of future autonomous robotic spacecraft (e.g., orbiter(s), balloon(s), surface/lake lander(s), rover(s)) that will be deployed for the exploration of Titan.

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Lunine, Jonathan I.0000-0003-2279-4131
Additional Information:© 2010 Elsevier Ltd. Received 25 May 2009; revised 15 November 2009; accepted 16 December 2009. Available online 6 January 2010. The authors wish to thank Sebastien Rodriguez for his thoughtful review comments that helped improve the manuscript.
Subject Keywords:Autonomous systems; Titan; Cryovolcanism; Artificial Intelligence; Fuzzy cognitive maps; Planetary exploration
Issue or Number:5
Record Number:CaltechAUTHORS:20100527-074700162
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:18468
Deposited By: Tony Diaz
Deposited On:01 Jun 2010 04:20
Last Modified:09 Mar 2020 13:19

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