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GENETIC OPTIMIZATION FOR ODOMETRY CALIBRATION OF TRICYCLE TOPOLOGY MOBILE ROBOTS

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JANUARY-DECEMBER 2017   -  Volume: 4 -  Pages: [19 p.]

DOI:

https://doi.org/10.6036/NT8079

Authors:

JULIO CESAR MARTINEZ ROMO
-
FRANCISCO LUNA ROSAS
- VALENTIN LOPEZ RIVAS - RICARDO MENDOZA GARCIA -
MARIO ALBERTO RODRIGUEZ DIAZ

Disciplines:

  • INFORMATION TECHNOLOGY AND KNOWLEDGE (INTELIGENCIA ARTIFICIAL Y SIMULACION )

Downloads:   46

How to cite this paper:  
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Received Date :   8 June 2016

Reviewing Date :   15 September 2016

Accepted Date :   20 March 2017


Key words:
optimización genética, robots móviles, calibración odométrica, genetic optimization, mobile robots, odometry calibration
Article type:
ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:
RESEARCH ARTICLES

ABSTRACT:
This paper presents a method for odometry calibration of tricycle topology mobile robots, which was focused on Automatic Guided Vehicle (AGV) . Odometry calibration for AGVs has been an open problem since the mobile robots inception. Basically, in this problem an AGV must have/know its position [x, y] and orientation [?] - broadly known as Pose- regarding to a starting point. Odometry calibration consists in determining the effective diameter of the AGV’s rear-wheels [k1, k2] and length of the axis between them [b]. These AGV parameters are used in a mathematical model to accurate calculate its position and orientation. The provided method get pulses from optical incremental-encoders (located at AGVs’ rear-wheels) in real-time, which are then used by a Genetic Algorithm to optimally determine the vector [k1, k2, b]. Obtained results suggested an absolute error of 1.5% (Max) for the pose calculation [x, y, ?] considering trajectories (straight and curved paths) up to 70 mts .

Key Words: genetic optimization, mobile robots, odometry calibration

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