Control and Machine Intelligence for System Autonomy

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Abstract

Autonomous systems evolve from control systems by adding functionalities that increase the level of system autonomy. It is very important to the research in the field that autonomy be well defined and so in the present paper a precise, useful definition of autonomy is introduced and discussed. Autonomy is defined as the ability of the system to attain a set of goals under a set of uncertainties. This leads to the notion of degrees or levels of autonomy. The Quest for Autonomy in engineered systems throughout the centuries is noted, connections to research work of 30 years ago are made and a hierarchical functional architecture for autonomous systems together with needed functionalities are outlined. Adaptation and Learning, which are among the most important functions in achieving high levels of autonomy are then highlighted and recent research contributions are briefly discussed.

Keywords

Autonomy Machine intelligence Adaptation and learning 

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.The Department of Electrical EngineeringUniversity of Notre DameNotre DameUSA

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