UAV bezier curve maneuver planning using Genetic Algorithm

Affiani Machmudah, Setyamartana Parman, Azman Zainuddin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

This paper presents Unmanned Aerial Vehicle (UAV) path planning using a Genetic Algorithm (GA) in a static environment at constant altitude. The cubic Bezier curve is used as path reference. The GA will find a proper control points position such that a minimum-length feasible path will be achieved. An optimization objective is a minimum path length with constraints. There are two constraints that must be satisfied, a free collision and a minimum turning radius. Fuzzy rules are applied in fitness function to satisfy these constraints. It needs to detect collisions after the curvature is satisfied. Results show that the proposed algorithm succeeded to find the goal path.

Original languageEnglish
Title of host publicationProceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 - Companion Publication
Pages2019-2022
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 - Portland, OR, United States
Duration: 7 Jul 201011 Jul 2010

Publication series

NameProceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 - Companion Publication

Conference

Conference12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010
Country/TerritoryUnited States
CityPortland, OR
Period7/07/1011/07/10

Keywords

  • Bezier curve
  • Genetic Algorithm
  • Maneuver planning

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