Q-Learning Algorithm for a Mobile Robot Obstacle Avoidance in an Unknown Environment Based on Artificial Neural Networks
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2011
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Prof. K.-D. Bouzakis
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In this paper neural network representation for the Q-learning algorithm of a mobile robot is presented. The property of adaptability in modern intelligent manufacturing environments is the significant advantage comparing with the traditional designed facilities. Presented approach characterizes its efficiency and simplicity considering the learning process of the intelligent agent - a mobile robot. Experience gathered from the external sensors in an obstacle avoidance task presents the input of the neural network, enabling the mobile robot to learn the value of the selected actions as the output of the neural network, gradually improving its behaviour. If the more learning epochs are conducted mobile robot could became autonomous, which can
be crucial advantage for the 21st century manufacturing systems.
Keywords:
Q-learning / Artificial neural networks / Intelligent mobile robot / Obstacle avoidance / Sensor processing / Mobile robot / Intelligent manufacturing environment / Intelligent agent / Autonomous robot behavior / 21st century manufacturing systemsSource:
Proceedings of the 4th International Conference on Manufacturing Engineering (ICMEN 2011), 2011, 431-440Publisher:
- The Aristotle University of Thessaloniki
Funding / projects:
- An innovative ecologically based approach to implementation of intelligent manufacturing systems for production of sheet metal parts (RS-MESTD-Technological Development (TD or TR)-35004)
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Mašinski fakultetTY - CONF AU - Miljković, Zoran AU - Mitić, Marko AU - Babić, Bojan AU - Diryag, Ali PY - 2011 UR - https://machinery.mas.bg.ac.rs/handle/123456789/4949 AB - In this paper neural network representation for the Q-learning algorithm of a mobile robot is presented. The property of adaptability in modern intelligent manufacturing environments is the significant advantage comparing with the traditional designed facilities. Presented approach characterizes its efficiency and simplicity considering the learning process of the intelligent agent - a mobile robot. Experience gathered from the external sensors in an obstacle avoidance task presents the input of the neural network, enabling the mobile robot to learn the value of the selected actions as the output of the neural network, gradually improving its behaviour. If the more learning epochs are conducted mobile robot could became autonomous, which can be crucial advantage for the 21st century manufacturing systems. PB - The Aristotle University of Thessaloniki C3 - Proceedings of the 4th International Conference on Manufacturing Engineering (ICMEN 2011) T1 - Q-Learning Algorithm for a Mobile Robot Obstacle Avoidance in an Unknown Environment Based on Artificial Neural Networks EP - 440 SP - 431 UR - https://hdl.handle.net/21.15107/rcub_machinery_4949 ER -
@conference{ author = "Miljković, Zoran and Mitić, Marko and Babić, Bojan and Diryag, Ali", year = "2011", abstract = "In this paper neural network representation for the Q-learning algorithm of a mobile robot is presented. The property of adaptability in modern intelligent manufacturing environments is the significant advantage comparing with the traditional designed facilities. Presented approach characterizes its efficiency and simplicity considering the learning process of the intelligent agent - a mobile robot. Experience gathered from the external sensors in an obstacle avoidance task presents the input of the neural network, enabling the mobile robot to learn the value of the selected actions as the output of the neural network, gradually improving its behaviour. If the more learning epochs are conducted mobile robot could became autonomous, which can be crucial advantage for the 21st century manufacturing systems.", publisher = "The Aristotle University of Thessaloniki", journal = "Proceedings of the 4th International Conference on Manufacturing Engineering (ICMEN 2011)", title = "Q-Learning Algorithm for a Mobile Robot Obstacle Avoidance in an Unknown Environment Based on Artificial Neural Networks", pages = "440-431", url = "https://hdl.handle.net/21.15107/rcub_machinery_4949" }
Miljković, Z., Mitić, M., Babić, B.,& Diryag, A.. (2011). Q-Learning Algorithm for a Mobile Robot Obstacle Avoidance in an Unknown Environment Based on Artificial Neural Networks. in Proceedings of the 4th International Conference on Manufacturing Engineering (ICMEN 2011) The Aristotle University of Thessaloniki., 431-440. https://hdl.handle.net/21.15107/rcub_machinery_4949
Miljković Z, Mitić M, Babić B, Diryag A. Q-Learning Algorithm for a Mobile Robot Obstacle Avoidance in an Unknown Environment Based on Artificial Neural Networks. in Proceedings of the 4th International Conference on Manufacturing Engineering (ICMEN 2011). 2011;:431-440. https://hdl.handle.net/21.15107/rcub_machinery_4949 .
Miljković, Zoran, Mitić, Marko, Babić, Bojan, Diryag, Ali, "Q-Learning Algorithm for a Mobile Robot Obstacle Avoidance in an Unknown Environment Based on Artificial Neural Networks" in Proceedings of the 4th International Conference on Manufacturing Engineering (ICMEN 2011) (2011):431-440, https://hdl.handle.net/21.15107/rcub_machinery_4949 .