Path Planning for Differential Drive Mobile Robot to Avoid Static Obstacles Collision using Modified Crossover Genetic Algorithm

Nia Saputri Utami, Achmad Jazidie, Rusdhianto Effendi Abdul Kadier

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

6 Citations (Scopus)

Abstract

Autonomous mobile robots such as differential drive mobile robots really need an intelligent navigation system that is able to avoid collisions with any obstacle from the starting point to the destination point. These collisions can be avoided by planning a collision-free path first. This study uses a modified genetic algorithm method to planning collision-free paths with static obstacles. Modification of the genetic algorithm is carried out on the crossover process by making rules that the fitness value of the progeny should be compared with fitness value of the parents. The chromosome with the best fitness value will be taken and used for the mutation process. Meanwhile the chromosome with poor fitness value will be completely ignored. Several experiments were carried out to achieve the desired criterion such as shortest path and fast execution time. The simulation result shows that the modified crossover genetic algorithm is able to generate optimal solutions based on the desired criterion.

Original languageEnglish
Title of host publicationProceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages282-287
Number of pages6
ISBN (Electronic)9781728137490
DOIs
Publication statusPublished - Aug 2019
Event2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019 - Surabaya, Indonesia
Duration: 28 Aug 201929 Aug 2019

Publication series

NameProceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019

Conference

Conference2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
Country/TerritoryIndonesia
CitySurabaya
Period28/08/1929/08/19

Keywords

  • Genetic Algorithm
  • differential drive mobile robot
  • path planning

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