Path planning of mobile robot using neural network

In this paper, the authors present an effective method to achieve both obstacle-avoidance and target-tracking for an autonomous mobile robot in an indoor environment. They employ a wall following algorithm using neural network pattern recognition to avoid obstacles. An autonomous mobile robot reache...

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Bibliographic Details
Published inISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No.99TH8465) Vol. 3; pp. 979 - 983 vol.3
Main Authors Il-Kyun Jung, Ki-Bum Hong, Suk-Kyo Hong, Soon Chan Hong
Format Conference Proceeding
LanguageEnglish
Published IEEE 1999
Subjects
Backpropagation algorithms
Decision making
Equations
Humans
Indoor environments
Mobile robots
Neural networks
Path planning
Robot kinematics
Testing
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Summary:In this paper, the authors present an effective method to achieve both obstacle-avoidance and target-tracking for an autonomous mobile robot in an indoor environment. They employ a wall following algorithm using neural network pattern recognition to avoid obstacles. An autonomous mobile robot reaches a given goal target by tracking algorithm. In case obstacles are detected by sonar sensors, an autonomous mobile robot avoids collision with obstacles by wall following algorithm. They propose a simple making method to avoid being trapped in a local minima which was a serious problem in local path planning. Simulation results using mobile robot demonstrate that the proposed algorithms are well suited to the obstacle-avoidance using wall-following and the path planning task for target-tracking.
ISBN:0780356624
9780780356627
DOI:10.1109/ISIE.1999.796750