Automatic navigation of mobile robots in unknown environments

Citation

Motlagh, Omid Reza Esmaeili and Nakhaeinia, Danial and Tang, Sai Hong and Karasfi, Babak and Khaksar, Weria (2014) Automatic navigation of mobile robots in unknown environments. Neural Computing & Applications, 24 (7-8). pp. 1569-1581. ISSN 0941-0643; ESSN: 1433-3058

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 planning from the first till the third path planning trial in a sample environment. Analysis of the results, limitations, and recommendations is included for future work.

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Official URL or Download Paper: http://link.springer.com/article/10.1007%2Fs00521-...

Additional Metadata

Item Type:	Article
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1007/s00521-013-1393-z
Publisher:	Springer
Keywords:	Local navigation; Reinforcement learning; Associative memory
Depositing User:	Nabilah Mustapa
Date Deposited:	26 Jul 2015 02:50
Last Modified:	06 Oct 2015 03:26
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1007/s00521-013-1393-z
URI:	http://psasir.upm.edu.my/id/eprint/36601
Statistic Details:	View Download Statistic

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