David Abad Perez;Basil Mohammed Al-Hadithi;Victor Cadix Martin
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Navigation of mobile robots using neural networks and genetic algorithms
The navigation of robots has been a subject of widespread interest over the last few decades. In the previous years, traditional methods based on mathematical equations were used, and there has been an evolution towards the use of methods based on artificial intelligence. Two of which have been used in this work: neural networks and genetic algorithms. Neural networks are used as a machine learning model to teach the robot to move from any starting point to a goal, avoiding obstacles along the way. However, this model needs an algorithm to learn how to carry out this activity, which is what the genetic algorithm will be used for. Furthermore, this method of navigation will be compared with the traditional method based on potential fields, where it can be observed how this new method based on artificial intelligence improves and solves some typical problems of the old methods, such as the tendency to get stuck in local minima.
期刊介绍:
IEEE Latin America Transactions (IEEE LATAM) is an interdisciplinary journal focused on the dissemination of original and quality research papers / review articles in Spanish and Portuguese of emerging topics in three main areas: Computing, Electric Energy and Electronics. Some of the sub-areas of the journal are, but not limited to: Automatic control, communications, instrumentation, artificial intelligence, power and industrial electronics, fault diagnosis and detection, transportation electrification, internet of things, electrical machines, circuits and systems, biomedicine and biomedical / haptic applications, secure communications, robotics, sensors and actuators, computer networks, smart grids, among others.