Three-dimensional path planning for unmanned aerial vehicles based on multi-objective genetic algorithm

Multi-objective formulations are realistic models for many complex engineering optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with r...

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Bibliographic Details
Published inProceedings of the 33rd Chinese Control Conference pp. 8617 - 8621
Main Authors Hongtao Tao, Zheng Wang, Jianxun Li
Format Conference Proceeding
LanguageEnglish
Published TCCT, CAA 01.07.2014
Subjects
evolutionary computation
Genetic algorithm
Genetic algorithms
Genetics
Linear programming
Multi-objective optimization
Optimization
Pareto-ranking approaches
Path planning
Sociology
Statistics
unmanned aerial vehicles
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Summary:Multi-objective formulations are realistic models for many complex engineering optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. This paper presents a genetic algorithm (GA) specifically for problems with multiple objectives. It differs primarily from traditional GA by using specialized mechanisms to promote solution diversity. Then the genetic algorithm approach is applied to three-dimensional path planning for unmanned aerial vehicles (UAVs). Specially, several mutation operators are extended and new mutation operators are introduced for path planning based on the modified problems of traditional path planning. The objective of the proposed mutation operator is to expel the solutions out of restricted area. Experiment results show the effectiveness of the proposed GA approach.
ISSN:2161-2927
DOI:10.1109/ChiCC.2014.6896447