Dr. Jeffrey S. Kargel Profile

Dr. Jeffrey S. Kargel

at Univ of Arizona

SPIE Involvement:

Author

Proceedings Article | 15 April 2008 Paper

Forward and inverse models for photon transport in soil-ice mixtures and their application to the problem of retrieving optical properties of planetary surfaces

Paolo Picca, Roberto Furfaro, Jeffrey Kargel, Barry Ganapol

Proceedings Volume 6960, 69600O (2008) https://doi.org/10.1117/12.777479

KEYWORDS: Optical properties, Scattering, Radiative transfer, Photon transport, Reflectivity, Data modeling, Artificial neural networks, Mathematical modeling, Remote sensing, Inverse problems

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Proceedings Article | 15 April 2008 Paper

Granular processes on Itokawa, a small near-Earth asteroid: implications for resource utilization

Hideaki Miyamoto, Jeffrey Kargel, Wolfgang Fink, Roberto Furfaro

Proceedings Volume 6960, 69600I (2008) https://doi.org/10.1117/12.784634

KEYWORDS: Asteroids, Space operations, Particles, Image resolution, Robotics, Metals, Head, Space robots, Mining, Solar system

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Proceedings Article | 15 April 2008 Paper

Robotic resource exploration is a key to human expansion through the cosmos

Jeffrey Kargel, Wolfgang Fink, Roberto Furfaro, Hideaki Miyamoto

Proceedings Volume 6960, 69600F (2008) https://doi.org/10.1117/12.784643

KEYWORDS: Mars, Asteroids, Manufacturing, Robotics, Solar system, Minerals, Stars, Planets, Mining, Metals

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Proceedings Article | 15 April 2008 Paper

Intelligent systems for the autonomous exploration of Titan and Enceladus

Roberto Furfaro, Jonathan Lunine, Jeffrey Kargel, Wolfgang Fink

Proceedings Volume 6960, 69600A (2008) https://doi.org/10.1117/12.777643

KEYWORDS: Fuzzy systems, Fuzzy logic, Reconnaissance, Artificial intelligence, Reconnaissance systems, Intelligence systems, Data acquisition, Satellites, Solar system, Methane

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Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific findings is highest. Generally, the level of needed automation is heavily influenced by the distance between Earth and the robotic explorer(s) (e.g. spacecraft(s), rover(s), and balloon(s)). Therefore, planning missions to the outer satellites mandates the analysis, design and integration within the mission architecture of semi- and/or completely autonomous intelligence systems. Such systems should (1) include software packages that enable fully automated and comprehensive identification, characterization, and quantification of feature information within an operational region with subsequent target prioritization and selection for close-up reexamination; and (2) integrate existing information with acquired, "in transit" spatial and temporal sensor data to automatically perform intelligent planetary reconnaissance, which includes identification of sites with the highest potential to yield significant geological and astrobiological information. In this paper we review and compare some of the available Artificial Intelligence (AI) schemes and their adaptation to the problem of designing expert systems for onboard-based, autonomous science to be performed in the course of outer satellites exploration. More specifically, the fuzzy-logic framework proposed is analyzed in some details to show the effectiveness of such a scheme when applied to the problem of designing expert systems capable of identifying and further exploring regions on Titan and/or Enceladus that have the highest potential to yield evidence for past or present life. Based on available information (e.g., Cassini data), the current knowledge and understanding of Titan and Enceladus environments is evaluated to define a path for the design of a fuzzy-based system capable of reasoning over collected data and capable of providing the inference required to autonomously optimize future outer satellites explorations.

Conference Committee Involvement (1)

Space Exploration Technologies

17 March 2008 | Orlando, Florida, United States

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