A genetic-algorithm-based approach to UAV path planning problem

Authors:
Xiao-Guang Gao;Xiao-Wei Fu;Da-Qing Chen
Affiliations:
School of Electronic and Information, Northwestern Polytechnical University, Xi'An, China;School of Electronic and Information, Northwestern Polytechnical University, Xi'An, China;Dept. of Info Systems & IT, London South Bank University, London, UK
Venue:
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Year:
2005

Citing 2
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Abstract

This paper presents a genetic-algorithm-based approach to the problem of UAV path planning in dynamic environments. Variable-length chromosomes and their genes have been used for encoding the problem. We model the vehicle path as a sequence of speed and heading transitions occurring at discrete times, and this model specifically contains the vehicle dynamic constraints in the generation of trial solutions. Simulation studies have shown that the proposed algorithm is effective in finding a near-optimal obstacle-free path in a dynamically changing environment, and the algorithm can guarantee that all candidate solutions lie within a feasible and reachable path space.