Optimal Trajectory Path Generation for Jointed Structure of Excavator using Genetic Algorithm

Ggyebong Jang, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose an algorithm to generate optimal trajectory path considering the complex operating environment of excavator front part composed of the boom, arm, and bucket by using genetic algorithm. In order to express motion in space, we propose a method of coordinate plane space of grid cell, and define the fitness value by path distance. After generating chromosome candidates for each motion unit based on the polygonal structure of the front part of the excavator, we calculate the fitness value about each chromosome. The crossover and mutation operations between the chromosomes selected through roulette wheel of top 20% are repeatedly performed to generate paths with optimal fitness values. This paper verifies the structural analysis of the front part of excavator and the utility of the genetic algorithm to optimize the path in the grid space.

Original languageEnglish
Title of host publication2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1953-1959
Number of pages7
ISBN (Electronic)9781728121536
DOIs
Publication statusPublished - 2019 Jun
Event2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, New Zealand
Duration: 2019 Jun 102019 Jun 13

Publication series

Name2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

Conference

Conference2019 IEEE Congress on Evolutionary Computation, CEC 2019
CountryNew Zealand
CityWellington
Period19/6/1019/6/13

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Modelling and Simulation

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