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Meeting	ACGS Committee Meeting 96 - Hilton Head - October 2005
Agenda Location	7 SUBCOMMITTEE E - FLIGHT, PROPULSION AND AUTONOMOUS VEHCILE CONTROL SYSTEMS 7.2 Intelligent Autonomy for Multiple Naval Unmanned Vehicles
Title	Intelligent Autonomy for Multiple Naval Unmanned Vehicles
Presenter	Marc Steinberg
Affiliation	Naval Air Systems Command
Available Downloads*	presentation
	Downloads are available to members who are logged in and either Active* or attended this meeting.
Abstract	The intelligent autonomy effort is focused on developing and demonstrating technology to reduce the need for human intervention for unmanned systems including unmanned air, undersea, and surface vehicles. This includes enabling highly automated dynamic retasking and fully autonomous dynamic replanning for individual unmanned vehicles and teams of up to five to ten heterogeneous unmanned vehicles. Initial experiments have been completed using both real vehicles and medium and high-fidelity unmanned air and undersea vehicle models in a simulated warfare environment. Simulation experiments included integration of multiple intelligent autonomy capabilities including multi-vehicle task allocation, dynamic replanning under constraints, lower level autonomous vehicle control, monitors for assessing contingencies that could require a change in plans, management of situation awareness data, operator alert management, and a mixed-initiative operator interface. Testing was done both non-real-time and with Navy and Marine Corps operators in-the-loop. In addition, in-water demonstrations were completed in both a river and a harbor environment using unmanned surface vehicles. The in-water demonstrations evaluated technology for autonomous maritime object detection, classification, tracking and mapping that will ultimately be integrated with dynamic replanning software for autonomous data collection. In addition, a multiple heterogeneous vehicle demonstration was performed at the McKenna Mission Operations in Urban Terrain (MOUT) site using small unmanned air and ground vehicles. Capabilities demonstrated at the MOUT site included specifying tasking for overall mission objectives and mapping them onto heterogeneous unmanned vehicles with different lower-level autonomy software, team planning mechanisms geared towards maximizing communications capabilities in adverse conditions while on the move, and automated acquisition of imagery data for situational awareness and synthesis into a more coherent picture for access by a human user. Finally, some lessons learned from the different designs, operator evaluations, and experiments were provided.