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Artificial neural networks-based simulation of obstacle detection with a mobile robot in a virtual environment

International Robotics & Automation Journal
Boris Crnokic,1 Ivan Peko,2 Miroslav Grubisic3


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.


obstacle detection, mobile robot, artificial neural networks, virtual simulation