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Evolutionary trajectory planner for multiple UAVs in realistic scenarios

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Besada Portas, Eva and Torre Cubillo, Luis de la and Cruz García, Jesús Manuel de la and Andrés Toro, Bonifacio de (2010) Evolutionary trajectory planner for multiple UAVs in realistic scenarios. IEEE Transactions on Robotics, 26 (4). pp. 619-634. ISSN 1552-3098

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5471080


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Abstract

This paper presents a path planner for multiple unmanned aerial vehicles (UAVs) based on evolutionary algorithms (EAs) for realistic scenarios. The paths returned by the algorithm fulfill and optimize multiple criteria that 1) are calculated based on the properties of real UAVs, terrains, radars, and missiles and 2) are structured in different levels of priority according to the selected mission. The paths of all the UAVs are obtained with the multiple coordinated agents coevolution EA (MCACEA), which is a general framework that uses an EA per agent (i.e., UAV) that share their optimal solutions to coordinate the evolutions of the EAs populations using cooperation objectives. This planner works offline and online by means of recalculating parts of the original path to avoid unexpected risks while the UAV is flying. Its search space and computation time have been reduced using some special operators in the EAs. The successful results of the paths obtained in multiple scenarios, which are statistically analyzed in the paper, and tested against a simulator that incorporates complex models of the UAVs, radars, and missiles, make us believe that this planner could be used for real-flight missions.


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© 2010 IEEE. This work was supported by the Community of Madrid under Project "COSICOLOGI" S-0505/DPI-0391, by the Spanish Ministry of Education and Science under Project DPI2006-15661-C02-01 and Project DPI2009-14552-C02-01, and by the European Aeronautic Defense and Space Company (Construcciones Aeronauticas Sociedad Anonima) under Project 353/2005. The work of E. Besada-Portas was supported by the Spanish Postdoctoral Grant EX-2007-0915 associated with the Prince of Asturias Endowed Chair of the University of New Mexico, University of New Mexico, Albuquerque, NM. This paper was presented in part at the Genetic Evolutionary Computation Conference, Atlanta, GA, 2008, and in part at the 8th International FLINS Conference, Madrid, Spain, 2008.

Uncontrolled Keywords:Algorithm-Based Approach, Unmanned Air Vehicles, Aerial Vehicles, Optimization, Aircraft Aerial Robotics, Multiobjective Evolutionary Algorithms (EAs), Path Planning for Multiple Mobile Robot Systems
Subjects:Sciences > Computer science > Robotics
Sciences > Computer science
ID Code:21363
Deposited On:06 Jun 2013 10:45
Last Modified:07 Jul 2015 08:51

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