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Recognition System by Using Machine Vision Tools and Machine Learning Techniques for Mobile Robots
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Author(s): Jesús Elias Miranda Vega (Polytechnic University of Baja California, Mexico), Anastacio González Chaidez (Polytechnic University of Baja California, Mexico), Cuauhtémoc Mariscal García (Faculty of Engineering, Autonomous University of Baja California, Mexico), Moisés Rivas López (Polytechnic University of Baja California, Mexico), Wendy Flores Fuentes (Faculty of Engineering, Autonomous University of Baja California, Mexico)and Oleg Sergiyenko (Engineering Institute, Autonomous University of Baja California, Mexico)
Copyright: 2021
Pages: 30
Source title:
Examining Optoelectronics in Machine Vision and Applications in Industry 4.0
Source Author(s)/Editor(s): Oleg Sergiyenko (Autonomous University of Baja California, Mexico), Julio C. Rodriguez-Quiñonez (Autonomous University of Baja California, Mexico)and Wendy Flores-Fuentes (Autonomous University of Baja California, Mexico)
DOI: 10.4018/978-1-7998-6522-3.ch009
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Abstract
The systems based on image recognition play an important role in many cases where inspection methods are critical for industrial processes. Machine vision is required in industry for monitoring and detecting objects in real-time applications. Industrial robots are increasingly used in a variety of industries and applications such as manipulators and mobile robots. These devices are necessary for dangerous work conditions and tasks that humans cannot do; however, these industrial robots can also do some human activities such as transport material, select, and identify objects. In order to substitute human capabilities is no easy task. Nevertheless, the use of artificial intelligence has been replacing some human activities for increased productivity. By supporting machine learning technologies, this chapter presents a k nearest neighbors' algorithm for image classification of mobile robots to detect and recognize objects.
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