Open AccessA blending crossover differential evolution approach to camera space manipulation parameter optimization
Author(s) -
Yu Xie,
Zhao Chun-xia,
Haofeng Zhang,
Xuejun Yan,
Debao Chen
Publication year - 2015
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.64.020701
Subject(s) - crossover , differential evolution , flattening , parameter space , computer science , evolutionary algorithm , fitness function , differential (mechanical device) , set (abstract data type) , function (biology) , algorithm , artificial intelligence , mathematics , genetic algorithm , physics , geometry , astronomy , machine learning , evolutionary biology , biology , thermodynamics , programming language
A blending crossover differential evolution algorithm is proposed to increase the precision of camera-space manipulation (CSM) system. In this approach, six view parameters and flattening parameter are assembled into a single parameter of blending crossover differential evolution; the positioning precision of camera-space manipulation is set to be a fitness function.The CSM system can obtain the optimal parameter combination by evolutionary iteration.Experimental results of a virtual robot system show the robot positioning precision is improved by blending crossover differential evolution algorithm.