NDLI: Evolutionary Trajectory Planner for Multiple UAVs in Realistic Scenarios

Content Provider	IEEE Xplore Digital Library
Author	Besada-Portas, E. de la Torre, L. de la Cruz, J.M. de Andrés-Toro, B.
Copyright Year	2004
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.
Sponsorship	IEEE Robotics and Automation Society
Starting Page	619
Ending Page	634
Page Count	16
File Size	1147348
File Format	PDF
ISSN	15523098
Volume Number	26
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Unmanned aerial vehicles Evolutionary computation Mobile robots Radar Missiles Path planning Remotely operated vehicles Constraint optimization Testing Computational modeling path planning for multiple mobile robot systems Aerial robotics multiobjective evolutionary algorithms (EAs)
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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