We study the mixed human-robot team design in a system theoretic settingusing the context of a surveillance mission. The three key coupled componentsof a mixed team design are (i) policies for the human operator, (ii) policiesto account for erroneous human decisions, and (iii) policies to control theautomaton. In this paper, we survey elements of human decision-making,including evidence aggregation, situational awareness, fatigue, and memoryeffects. We bring together the models for these elements in humandecision-making to develop a single coherent model for human decision-making ina two-alternative choice task. We utilize the developed model to designefficient attention allocation policies for the human operator. We propose ananomaly detection algorithm that utilizes potentially erroneous decision by theoperator to ascertain an anomalous region among the set of regions surveilled.Finally, we propose a stochastic vehicle routing policy that surveils ananomalous region with high probability. Our mixed team design relies on thecertainty-equivalent receding-horizon control framework.
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