Application of genetic algorithms to robot kinematics calibration

For an industrial robots with unknown parameters, on the basis of preliminary measurement and data of the Cartesian and joints coordinates which are shown on the FlexPendant, the kinematic parameters is identified by using genetic algorithms and accurate kinematics modeling of the robot is established. Experimental data could prove the validity of this method.

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Hierarchical time-optimal control of a continuous copolymerization reactor during start-up or grade change operation using genetic algorithms

Computers & Chemical Engineering ◽

10.1016/s0098-1354(97)00186-5 ◽

1997 ◽

Vol 21 (1-2) ◽

pp. S1037-S1042

Author(s):

H Moo

Keyword(s):

Optimal Control ◽

Genetic Algorithms ◽

Time Optimal Control ◽

Grade Change ◽

Start Up ◽

Time Optimal ◽

Change Operation ◽

Grade Change Operation

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Genetic Algorithms—a Tool for OR?

Journal of the Operational Research Society ◽

10.1057/palgrave.jors.0470406 ◽

1996 ◽

Vol 47 (4) ◽

pp. 550-561 ◽

Cited By ~ 2

Author(s):

Kathryn A Dowsland

Keyword(s):

Genetic Algorithms

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Road Horizontal Alignment Design Method for Continuous Loop Area in Autonomous Vehicles Proving Ground Based on Genetic Algorithms

CICTP 2020 ◽

10.1061/9780784483053.163 ◽

2020 ◽

Author(s):

Junyi Chen ◽

Rubing Li ◽

Xingyu Xing ◽

Lu Xiong

Keyword(s):

Genetic Algorithms ◽

Autonomous Vehicles ◽

Design Method ◽

Horizontal Alignment ◽

Loop Area

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Enhanced Artificial Intelligent Method for Representing the Photonic Crystal Fiber Profile Index

Al-Kitab Journal for Pure Sciences ◽

10.32441/kjps.v1i1.87 ◽

2018 ◽

Vol 1 (1) ◽

pp. 2-19

Author(s):

Mahmood Sh. Majeed ◽

Raid W. Daoud

Keyword(s):

Genetic Algorithms ◽

Photonic Crystal ◽

Photonic Crystal Fiber ◽

New Method ◽

Proper Solution ◽

Artificial Intelligent ◽

Crystal Fiber ◽

Fitness Value ◽

First Pass ◽

Crossover And Mutation

A new method proposed in this paper to compute the fitness in Genetic Algorithms (GAs). In this new method the number of regions, which assigned for the population, divides the time. The fitness computation here differ from the previous methods, by compute it for each portion of the population as first pass, then the second pass begin to compute the fitness for population that lye in the portion which have bigger fitness value. The crossover and mutation and other GAs operator will do its work only for biggest fitness portion of the population. In this method, we can get a suitable and accurate group of proper solution for indexed profile of the photonic crystal fiber (PCF).

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