Tasking human agents: A sigmoidal utility maximization approach for target identification in mixed teams of humans and UAVs

Michael Donohue, Cedric Langbort

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a general utility maximization framework, based on experimentally observed human specific speed-accuracy trade-offs, to account for and exploit some characteristics of human operators engaged in human/machine mixed teams and increase their performance. In particular, we consider instances where a human operator is tasked by image capturing machines and must render a decision based upon the images. We then study methods, based on exact Karush-Kuhn-Tucker (KKT) necessary conditions and sum-of-squares (SOS) relaxations, to try and solve the resulting non-concave maximization problem, and optimally allocate a human operator's time to identification tasks so as to maximize the probability of correct identification.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference and Exhibit
StatePublished - Dec 1 2009
EventAIAA Guidance, Navigation, and Control Conference and Exhibit - Chicago, IL, United States
Duration: Aug 10 2009Aug 13 2009

Publication series

NameAIAA Guidance, Navigation, and Control Conference and Exhibit

Other

OtherAIAA Guidance, Navigation, and Control Conference and Exhibit
Country/TerritoryUnited States
CityChicago, IL
Period8/10/098/13/09

ASJC Scopus subject areas

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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