Paper
2 May 2018 Finding common ground by unifying autonomy indices to understand needed capabilities
Trevor Bihl, Chadwick Cox, Todd Jenkins
Author Affiliations +
Abstract
Autonomous machines promise to reduce the workload of human operators by replacing some or all cognitive functions with intelligent software. However, development is retarded by disagreement among researchers at very basic levels, including what is meant by autonomy and how to achieve it. Clear definitions are few and no one has successfully bridged the gap between philosophical notions and engineering methods. A variety of autonomy measures are reviewed, highlighting their strengths and weaknesses. Various researchers have developed these autonomy measures to facilitate discussions of capabilities. These measures are also a means of comparing and contrasting autonomy approaches. We contend that any properly structured set of measures are not only useful for these functions, but it provides both a philosophical and practical justification, it outlines developmental steps, it suggests schematic constraints, and it implies requirements for tests. As such, we make recommendations for the further developments of autonomy measures.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Trevor Bihl, Chadwick Cox, and Todd Jenkins "Finding common ground by unifying autonomy indices to understand needed capabilities", Proc. SPIE 10641, Sensors and Systems for Space Applications XI, 106410G (2 May 2018); https://doi.org/10.1117/12.2303670
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Artificial intelligence

Unmanned vehicles

Psychology

Warfare

Micro unmanned aerial vehicles

Unmanned aerial vehicles

Unmanned combat air vehicles

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