NDLI: Evolution of a UAV Autonomy Classification Taxonomy

Content Provider	IEEE Xplore Digital Library
Author	Sholes, E.
Copyright Year	2007
Description	Author affiliation: Syst. Simulation Dev. Directorate, Redstone Arsenal (Sholes, E.)
Abstract	At PerMIS 2002, the Air Force Research Lab presented a paper entitled "Metrics Schmetrics", which presented the results of a research study on how to determine the autonomy level of a unmanned aerial vehicle (UAV). The striking point made by the author, given the obvious importance of the need to effectively evaluate and classify autonomous algorithms, was the general dearth of existing effective metrics and/or taxonomies to determine a UAVs autonomy level. To fill the void, the author presented a framework, referred to as the AFRL Autonomy Framework, which identified 10 autonomy control levels (ACLs) and presented the characteristics that differentiate the various levels. The purpose of this paper is to examine how the metrics presented have been applied and how they have evolved and expanded, in theory and practice, as a result of lessons learned during those applications. Specifically, the evolution in metrics development has culminated with the advent of an evaluation technique that blends emerging simulation technologies to create new unmanned aerial vehicle (UAV) autonomy assessment methods which take full advantage of visual virtual environments and statistical constructive simulations to examine the autonomy algorithm along the four dimensions of the Observe, Orient, Decide, Act (OODA) loop commonly applied by military aviators during the decision making process. This approach has been used over the last three years to evaluate emerging autonomy technologies from the Army's Unmanned Autonomous Collaborative Operations (UACO) Science and Technology program. This unique technique for testing UAV autonomy effectiveness is a significant advance in the UAV community. As autonomy algorithms proliferate to the point where multiple candidate algorithms are available for each platform, the ability to characterize the effectiveness of each autonomy algorithm will be critical to further for successful implementation of autonomous capability.
Starting Page	1
Ending Page	16
File Size	1535174
Page Count	16
File Format	PDF
ISBN	1424405246
ISSN	1095323X
DOI	10.1109/AERO.2007.352738
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Unmanned aerial vehicles Taxonomy Missiles Virtual environment Decision making Automotive engineering Systems engineering and theory Collaboration Testing Aerospace industry
Content Type	Text
Resource Type	Article
Subject	Aerospace Engineering Space and Planetary Science

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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