motlagh, o and nakhaeinia, n and tang, s.h. (2013) Automatic Navigation of Mobile Robots in Unknown Environments. Neural Computing and Applications. xxxx-xxxx. ISSN xxxx-xxxx
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Abstract
Online navigation with known target and unknown obstacles is an interesting problem in mobile robotics. This article presents a technique based on utilization of neural networks and reinforcement learning to enable a mobile robot to learn constructed environments on its own. The robot learns to generate efficient navigation rules automatically without initial settings of rules by experts. This is regarded as the main contribution of this work compared to traditional fuzzy models based on notion of artificial potential fields. The ability for generalization of rules has also been examined. The initial results qualitatively confirmed the efficiency of the model. More experiments showed at least 32% of improvement in path panning from the first till the third path planning trial in a sample environment. Analysis of the results, limitations and recommendations are included for future work.
Item Type: | Article |
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Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Manufacturing Engineering > Department of Robotics and Automation |
Depositing User: | Omid Motlagh |
Date Deposited: | 25 Jul 2013 00:16 |
Last Modified: | 28 May 2015 03:50 |
URI: | http://eprints.utem.edu.my/id/eprint/7577 |
Statistic Details: | View Download Statistic |
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