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|a Clare, Andrew S.
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|a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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|a Clare, Andrew S.
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|a Macbeth, Jamie C.
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|a Cummings, M. L.
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|a Macbeth, Jamie C.
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|a Cummings, M. L.
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|a Mixed-initiative strategies for real-time scheduling of multiple unmanned vehicles
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|b Institute of Electrical and Electronics Engineers (IEEE),
|c 2013-10-01T15:28:37Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/81258
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|a 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.
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|a United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship)
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|a en_US
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|a Article
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|t Proceedings of the American Control Conference (ACC), 2012
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