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Abstract

Two core challenges must be overcome to enable the wider use of robotic and uninhabited vehicles by personnel with limited training. These are robust and understandable autonomy and simplified, intuitive, and learnable human control mechanisms. Our research is based on the premise that investigation into computational models of human cognition, personality, communication, and emotion can be used to solve leading edge problems in robotic and uninhabited vehicle control. Specifically, it is hoped that Motive and Affect-based Robotic Control (MARC) can enhance collaboration between human controllers and robotic vehicles by enabling a motive and affect based control language and paradigm that more closely resembles that used by human dyads and teams in collaborative behavior. Results of our research indicate an improved ability of human controllers with minimal training to use a MARC prototype to control multiple UAV's in a simulated mission. Workload comparisons (Cooper-Harper and NASA-TLX) with a baseline control interface indicate a clear advantage to the MARC based system.

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Motive and Affect Based Control for Uninhabited Vehicles

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