West Virginia University (WVU) researchers have developed a genetic algorithm to mobilize unmanned aerial vehicles (UAVs) in team missions.
The technology enables a group of UAVs to fly autonomously to complete complex coordinated missions.
A researcher on the ground sets an area to be scanned by the UAV, and then selects different priority points for information-gathering. "The algorithm then sets what coordinates are surveyed by which UAVs, and determines a plan for them so that it also covers as much of the area as possible without depleting the battery life," says WVU professor Marjorie Darrah.
"Now that we are seeing how the Raven [UAV] is being used in many countries around the world--it's versatile, hand-launched, robust--we can encourage people to use the technology in new ways," Darrah notes.
Civilian projects also can use the algorithm to work with UAVs in teams--for example, the team approach could be useful for monitoring biological threats to agriculture, detecting fires, conducting transportation surveillance, and managing natural disasters.
WVU graduate student Marcela Mera Trujillo is working to use a similar genetic algorithm approach to employ various mapping techniques in order to capture images of structures from many different angles.
From University of West Virginia
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