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A Bayesian Framework for Landing Site Selection During Autonomous Spacecraft DescentThe success of a landed space exploration mission depends largely on the final landing site. Factors influencing site selection include safety, fuel-consumption, and scientific return. This paper addresses the problem of selecting the best available landing site based on these factors in real-time during autonomous spacecraft descent onto a planetary surface. The problem is modeled probabilistically using Bayesian Networks (BNs). BNs provide a means of representing the causal relationships between variables that impact the quality of a landing site. The final landing site is determined via probabilistic reasoning based on terrain safety derived from on-board sensors, available fuel based on spacecraft descent dynamics, and regions of interest defined by mission scientists.
Document ID
20060051765
Acquisition Source
Jet Propulsion Laboratory
Document Type
Preprint (Draft being sent to journal)
External Source(s)
Authors
Serrano, Navid
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
August 23, 2013
Publication Date
January 1, 2006
Subject Category
Space Transportation And Safety
Meeting Information
Meeting: Intelligent Robots and Systmes Conference (IROS)
Location: Beijing
Country: China
Start Date: October 9, 2006
End Date: October 15, 2006
Distribution Limits
Public
Copyright
Other
Keywords
entry, descent, landing (EDL)
autonomous spacecraft
terrain characterization
safe landing
robotics
Bayesian reasoning

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