Locating RF emitters with large UAV teams
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Multiple targets geolocation using SIFT and stereo vision on airborne video sequences
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Geolocation of Multiple Targets from Airborne Video Without Terrain Data
Journal of Intelligent and Robotic Systems
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In this paper we propose a novel cooperation control method for multiple Unmanned Aerial Vehicles (UAVs) to search, detect, and locate ground targets. We assume that our UAVs are only equipped with rudimentary angle of arrival sensors and the ground targets are mobile Radio Frequency (RF) emitters. In addition to the mobility, we assume our targets emit signals with random duration and frequency. Our cooperative UAVs function as a reconfigurable sensor network whose goal is to minimize target localization time and the target location error. The proposed control method extends our previous work on distributed control architecture [1] for multiple UAVs by introducing localized hierarchical control structures. Such structures are dynamically established by local leaders that autonomously emerge in response to individual sensor readings, allowing efficient coordination of activities among nearby UAVs. The sensor network uses Kalman filtering techniques to minimize the target location error and the target localization time by combining current and past captured sensor values from multiple UAVs. We validate our proposed control method with simulation results that illustrate its performance under varying levels of cooperation among the members of the sensor network.