The prolific development of Unmanned Aerial Vehicles (UAV’s) in recent years has the potential to provide tremendous advantages in military, commercial and law enforcement applications. While safety and performance take precedence in the development lifecycle, autonomous operations and, in particular, cooperative missions have the ability to significantly enhance the usability of these vehicles. The success of cooperative missions relies on the optimal allocation of targets while taking into consideration the resource limitation of each vehicle. The task allocation process can be centralized or decentralized. This effort presents the development of a real time target allocation algorithm that considers available stored energy in each vehicle while minimizing the communication between each UAV. The algorithm utilizes a nearest neighbor search algorithm to locate new targets with respect to existing targets. Simulations show that this novel algorithm compares favorably to the mixed integer linear programming method, which is computationally more expensive. The implementation of this algorithm on Arduino and Xbee wireless modules shows the capability of the algorithm to execute efficiently on hardware with minimum computation complexity.
|Commitee:||Aliasgari, Mehrdad, Shankar, Praveen|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 55/02M(E), Masters Abstracts International|
|Subjects:||Engineering, Aerospace engineering|
|Keywords:||Hardware implementation of task allocaiton, Knnsearch, Real time task allocation, Robust task allocation, Swarm of uav task allocation, Uav task allocation|
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