NDLI: UAV path planning method based on ant colony optimization

Content Provider	IEEE Xplore Digital Library
Author	Chao Zhang Ziyang Zhen Daobo Wang Meng Li
Copyright Year	2010
Description	Author affiliation: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 210016, China (Chao Zhang; Ziyang Zhen; Daobo Wang; Meng Li)
Abstract	A new UAV path planning method based on ant colony optimization (ACO) is presented. The target position is considered as the food source which the ants are going to find. The enemy defense region is considered as the searching area of the ants and is divided into equally spaced grids. The ants move to the destination node through several nodes on the grid region. The visibility function of ACO algorithm considers the enemy threats intensity on the paths and the distance to the destination node. The weighted sums of the flight path length, the threat cost and the maximum restriction of the yaw angle are considered as the evaluation function of ACO algorithm. The pheromone amounts on the paths are updated according to the evaluation function values. Therefore, the UAV optimal flight path is expressed by a group of node number, which is obtained by the ants finding the optimal route to the food source. The ACO algorithm based UAV path planning method is characterized as simple coding and good optimization guidance, and the simulation results also show its effectiveness.
Starting Page	3790
Ending Page	3792
File Size	149821
Page Count	3
File Format	PDF
ISBN	9781424451814
DOI	10.1109/CCDC.2010.5498477
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chaos Ant Colony Optimization Ant colony optimization Automation Navigation Radar tracking Educational institutions Path planning Particle swarm optimization Swarm Intelligence Path Planning Unmanned Aerial Vehicle Cost function Unmanned aerial vehicles
Content Type	Text
Resource Type	Article

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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