Navy asks for industry's help to establish effective screening and training for UAV pilots

Aug. 9, 2012
ARLINGTON, Va., 9 Aug. 2012. The U.S. Navy needs better ways to choose, train, and equip unmanned aerial vehicle (UAV) pilots, and is reaching out to industry for new technological approaches to do this -- particularly for medium-to-large UAVs like the AAI RQ-7 Shadow, the Northrop Grumman MQ-4C Broad Area Maritime Surveillance (BAMS) UAV, the Northrop Grumman MQ-8 Fire Scout unmanned helicopter, and future unmanned carrier-launched airborne surveillance and strike (UCLASS) aircraft.

ARLINGTON, Va., 9 Aug. 2012. The U.S. Navy needs better ways to choose, train, and equip unmanned aerial vehicle (UAV) pilots, and is reaching out to industry for new technological approaches to do this -- particularly for medium-to-large UAVs like the AAI RQ-7 Shadow, the Northrop Grumman MQ-4C Broad Area Maritime Surveillance (BAMS) UAV, the Northrop Grumman MQ-8 Fire Scout unmanned helicopter, and future unmanned carrier-launched airborne surveillance and strike (UCLASS) aircraft.

The Office of Naval Research issued a broad agency announcement (ONR BAA 12-011) in late July for the Unmanned Aerial Systems Interface, Selection, and Training Technologies (UASISTT) program to improve UAV control station interfaces, training technologies or selection tools.

Today's UAV control stations are not easy for UAV pilots to use, ONR researchers say, pointing out that despite advances in UAV capabilities in previous years, as many as 50 percent of today's UAV accidents are the fault of human operators. This problem, moreover, is only likely to get worse.

The Navy and Marine Corps are increasing their UAV purchases significantly, and these unmanned aircraft are complex. They blend automation with dynamic, decentralized control for a wide range of missions, often different from traditional manned aircraft missions.

The UASISTT program seeks to help the Navy and other U.S. military UAV operators develop a new kind of UAV pilot who has been chosen, trained, and equipped to process information effectively; work with cutting-edge technologies; work together with other UAV pilots; and manage the UAV operational workload on long missions.

Evidently military officials are finding that traditional manned aircraft pilot training and proficiency with complex video games are simply not enough to prepare tomorrow's UAV pilots. "Today, simply replicating the manned aviation select-train-equip approach is an inefficient solution at best and a potentially disastrous one at worst," Navy researchers say in the solicitation.

Researchers are finding that today's UAV operators must have skills more akin to the air traffic controller than to the manned aircraft pilot. UAV operators work in sensory-deprived conditions without the sights, sounds, and feel of manned aviation.

Instead, as automation technology advances, the role of the UAV operator will continue shifting towards mission management of several different UAVs, with demands for far more decision making, course of action planning, collaborative planning, and resource management than for stick-and-rudder piloting skills.

The ONR UASISTT program focuses on three technical areas: selecting UAV operators by forecasting candidate performance across UAVs and missions; designing realistic UAV operator simulation and training; and UAV control station human-machine interfaces.

ONR will conduct industry day briefings for the UASISTT program in Arlington, Va., on 17 Aug. Register by e-mail to the Navy's Brigid Jacobs at [email protected]

Companies interested in bidding on the UASISTT program should submit white papers by 10 Sept. 2012, give full-proposal oral presentations on 5 to 9 Nov. 2012, and submit full proposals by 7 Dec. 2012.

For questions or concerns, contact the Navy's Russelle Dunson by phone at 703-696-8375 or by e-mail at [email protected], or Joseph Cohn by phone at 703-696-2580 or by e-mail at [email protected].

More information is online at https://www.fbo.gov/spg/DON/ONR/ONR/ONRBAA12-011/listing.html.

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