<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Kinematic model is the basic aspect in robot design and motion planning. Kinematic models are idealized, however there exist certain specific aspects of particular robot or environment, so that during navigation, the robot can significantly deviate from the planned trajectory. To increase the accuracy of motions, kinematic model can be improved and to achieve that the artificial intelligence methods can be used. In case of fixed base robots different approaches are used to train kinematics, at the same time, for the mobile base robots it proves to be a more complicated task. The reason is that a mobile robot can move unbound with respect to environment thus it is difficult to control the platform without deviation from the target position, which leads to inaccuracy in the position estimate. This paper presents the method meant for improvement of the accuracy of motion of differential drive platform. Genetic programming is used to obtain the wheel velocity function, from which the coefficient, which describes different factor influence on motion, is obtained. As a result, the kinematic model of a particular platform for a particular task is obtained. This method is effective because the developed kinematic model is more specific than the general one.</p></abstract>

Kinematic model is the basic aspect in robot design and motion planning. Kinematic models are idealized, however there exist certain specific aspects of particular robot or environment, so that during navigation, the robot can significantly deviate from the planned trajectory. To increase the accuracy of motions, kinematic model can be improved and to achieve that the artificial intelligence methods can be used. In case of fixed base robots different approaches are used to train kinematics, at the same time, for the mobile base robots it proves to be a more complicated task. The reason is that a mobile robot can move unbound with respect to environment thus it is difficult to control the platform without deviation from the target position, which leads to inaccuracy in the position estimate. This paper presents the method meant for improvement of the accuracy of motion of differential drive platform. Genetic programming is used to obtain the wheel velocity function, from which the coefficient, which describes different factor influence on motion, is obtained. As a result, the kinematic model of a particular platform for a particular task is obtained. This method is effective because the developed kinematic model is more specific than the general one.

Use of Learning Methods to Improve Kinematic Models

Riga Technical University, Faculty of Computer Science and Information Technology, Institute of Applied Computer Systems

Applied Computer Systems

{"article-title":"Use of Learning Methods to Improve Kinematic Models"}

Kinematic model is the basic aspect in robot design and motion planning. Kinematic models are idealized, however there exist certain specific aspects of...

Use of Learning Methods to Improve Kinematic Models

Publié en ligne: 08 juin 2013

Pages: 73 - 79

DOI: https://doi.org/10.2478/acss-2013-0009

Mots clés
genetic programming, learning kinematic, mobile platforms

This content is open access.

Use of Learning Methods to Improve Kinematic Models

Publié en ligne: 08 juin 2013

Pages: 73 - 79

DOI: https://doi.org/10.2478/acss-2013-0009

Mots clésgenetic programming, learning kinematic, mobile platforms

This content is open access.

Mots clés
genetic programming, learning kinematic, mobile platforms