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Jianjun Peng, Hui Wang, Jiping Li and Chuanming Song

of Generative Processes from B-Rep Shapes and Application to Idealization Transformations. – Computer-Aided Design, Vol. 46 , 2014, pp. 79-89. 12. Zhu, Y., et al., Computing a Compact Spline Representation of the Medial Axis Transform of a 2D Shape. – Graphical Models, Vol. 76 , 2014, No 5, pp. 252-262. 13. Ahn, S., et al. Differentiation of Human Pluripotent Stem Cells into Medial Ganglionic Eminence vs Caudal Ganglionic Eminence Cells. – Methods, Vol. 101 , 2016, pp. 103-112. 14. Peng, J., R. Guo et al., Research and Application of NC

Open access

Xinyue Yang and Qinjian Yuan

methods, tools, and strategies, trying hard to get in touch with their consumers effectively and present idealized images of themselves. The interactive performance of interactive tools has a positive effect on the perception of interaction and the improvement of the customer relationship. For example, interactive websites lead to customers’ higher favorability toward the websites and greater flow state intensity ( Sicilia, Ruiz, & Munuera, 2005 ). Common interactive tools and their features are summarized in Table 1 . By adopting and developing all kinds of

Open access

Kintija Priedniece, Agris Nikitenko, Aleksis Liekna and Guntis Kulikovskis

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.