Mixed-initiative strategies for real-time scheduling of multiple unmanned vehicles

Advances in autonomy have made it possible to invert the typical operator-to-unmanned vehicle ratio so that a single operator can now control multiple heterogeneous Unmanned Vehicles (UVs). Real-time scheduling and task assignment for multiple UVs in uncertain environments will require the computati...

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Bibliographic Details
Main Authors: Clare, Andrew S. (Contributor), Macbeth, Jamie C. (Contributor), Cummings, M. L. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2013-10-01T15:28:37Z.
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Description
Summary:Advances in autonomy have made it possible to invert the typical operator-to-unmanned vehicle ratio so that a single operator can now control multiple heterogeneous Unmanned Vehicles (UVs). Real-time scheduling and task assignment for multiple UVs in uncertain environments will require the computational ability of optimization algorithms combined with the judgment and adaptability of human supervisors through mixed-initiative systems. The goal of this paper is to analyze the interactions between operators and scheduling algorithms in two human- in-the-loop multiple UV control experiments. The impact of real-time operator modifications to the objective function of an optimization algorithm for multi-UV scheduling is described. Results from outdoor multiple UV flight tests using a human-computer collaborative scheduling system are presented, which provide valuable insight into the impact of environmental uncertainty and vehicle failures on system effectiveness.
United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship)