Pregled bibliografske jedinice broj: 1272248
Artificial neural networks-based simulation of obstacle detection with a mobile robot in a virtual environment
Artificial neural networks-based simulation of obstacle detection with a mobile robot in a virtual environment // International Robotics & Automation Journal, 9 (2023), 2; 62-67 doi:10.15406/iratj.2023.09.00265 (međunarodna recenzija, članak, stručni)
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Naslov
Artificial neural networks-based simulation of
obstacle detection with a mobile robot in a
virtual environment
Autori
Crnokić, Boris ; Peko, Ivan ; Grubišić, Miroslav
Izvornik
International Robotics & Automation Journal (2574-8092) 9
(2023), 2;
62-67
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, stručni
Ključne riječi
obstacle detection ; mobile robot ; artificial neural networks ; virtual simulation
Sažetak
Mobile robot navigation is primarily a task that occurs in a real environment. However, simulating obstacles and robot movements in a virtual environment can provide significant advantages and yield good results, as demonstrated in this paper. By employing artificial neural networks (ANNs), it is possible to develop a trained system in a virtual environment that can detect obstacles using data collected from various sensors. In this study, infrared (IR) sensors and a camera were utilized to gather information from the virtual environment. The MatLab Simulink software package was used as a tool to train the artificial neural networks. Detection and avoidance of obstacles were simulated in the RobotinoSIM virtual environment.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
