Optimal flight path planner for an unmanned helicopter by evolutionary algorithms

L. Zhao, V. R. Murthy

Research output: Chapter in Book/Entry/PoemConference contribution

8 Scopus citations

Abstract

This paper presents an evolutionary method to develop an optimal flight path planner for an unmanned helicopter with initial, final states, and waypoint constraints under certain prescribed operational environment. The operational environment consists of concave and non-concave obstacles which are represented by different geometric shapes and their combinations. The minimum flight time is considered as the objective function in the optimization process. The stochastic universal sampling selection technique, mutation and crossover operators are implemented in the evolutionary method. Finally, the method is validated by applying to optimal flight path problems in highly constrained operational environments.

Original languageEnglish (US)
Title of host publicationCollection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2007
Pages3716-3739
Number of pages24
StatePublished - 2007
EventAIAA Guidance, Navigation, and Control Conference 2007 - Hilton Head, SC, United States
Duration: Aug 20 2007Aug 23 2007

Publication series

NameCollection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2007
Volume4

Other

OtherAIAA Guidance, Navigation, and Control Conference 2007
Country/TerritoryUnited States
CityHilton Head, SC
Period8/20/078/23/07

ASJC Scopus subject areas

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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