Open AccessLunar Rover Path Planning Based on Comprehensive Genetic Algorithm Based on Slip Prediction
Author(s) -
Lanfeng Zhou,
Liang Yang,
Hua Fang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1267/1/012097
Subject(s) - genetic algorithm , terrain , fitness function , motion planning , computer science , convergence (economics) , algorithm , mathematical optimization , path (computing) , stability (learning theory) , artificial intelligence , mathematics , machine learning , geography , cartography , economic growth , robot , economics , programming language
Aiming at the problem that the lunar rover path planning algorithm generally has slow convergence rate, falls into local optimal solution, neglects the mutual applicability of environment modeling technology and path planning algorithm, a comprehensive genetic algorithm based on virtual three-dimensional model is proposed. By setting the genetic factor unchanged, the terrain comprehensive cost function is added to set the fitness function. Using genetic algorithm and improved comprehensive genetic algorithm, after 100 simulation experiments, the improved comprehensive genetic algorithm has good search performance, fast convergence and high stability. The key words of this paper are as follows: path planning, terrain comprehensive cost function, genetic algorithm.