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Productive Information ForagingThis paper presents a new algorithm for autonomous on-line exploration in unknown environments. The objective of the algorithm is to free robot scientists from extensive preliminary site investigation while still being able to collect meaningful data. We simulate a common form of exploration task for an autonomous robot involving sampling the environment at various locations and compare performance with a simpler existing algorithm that is also denied global information. The result of the experiment shows that the new algorithm has a statistically significant improvement in performance with a significant effect size for a range of costs for taking sampling actions.
Document ID
20160011186
Acquisition Source
Ames Research Center
Document Type
Technical Memorandum (TM)
Authors
Furlong, P. Michael (SGT, Inc. Moffett Field, CA, United States)
Dille, Michael (SGT, Inc. Moffett Field, CA, United States)
Date Acquired
September 12, 2016
Publication Date
August 1, 2016
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Report/Patent Number
ARC-E-DAA-TN34778
NASA/TM-2016-219376
Funding Number(s)
TASK: Task 8
CONTRACT_GRANT: NNA14AA60C
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
exploration
information gain
sampling

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