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A modified genetic algorithm for global path planning of searching robot in mine disasters

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

Abstract

A modified genetic algorithm for global path planning of searching robot in mine disasters is proposed in this paper. The grid model is built based on the mine GIS (Geographic Information System) which can be obtained from the mine in advance. Using the position information feedback from the Ant Colony Optimization and priority grouping, we present a new efficient method to generate the initial population. Four traditional genetic operators and a fitness function are designed to find the optimum path planning. To avoid the premature, we make some changes to the mutation operators, and self-adaptively adjust the probabilities of crossover and mutation. The simulation is carried out in MATLAB, and the result verifies that it can acquire better collision-free path in higher speed.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Pages4936-4940
Number of pages5
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 - Changchun, China
Duration: 9 Aug 200912 Aug 2009

Publication series

Name2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009

Conference

Conference2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Country/TerritoryChina
CityChangchun
Period9/08/0912/08/09

Keywords

  • Genetic algorithm
  • Global path planning
  • Position information feedback and priority grouping
  • Searching robot
  • Self-adaptive probabilities

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