Abstract
Mobile robot path planning in a movement environment is an important problem. We studied acquisition of a path to a destination and multiple moving obstacles avoidance of a wheeled type robot. The paper proposes a method of path planning based on neural network and genetic algorithm. The avoidance action of a wheeled type robot is determined from the obstacle configuration, the robot’s self-state and destination information using a neural network. The design parameter of neural network is adjusted by using genetic algorithm.
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© 2009 Springer-Verlag Berlin Heidelberg
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Yamaguchi, T., Watanabe, Y. (2009). Multiple Moving Obstacles Avoidance for Wheeled Type Robots Using Neural Network. In: Budiyono, A., Riyanto, B., Joelianto, E. (eds) Intelligent Unmanned Systems: Theory and Applications. Studies in Computational Intelligence, vol 192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00264-9_11
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DOI: https://doi.org/10.1007/978-3-642-00264-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00263-2
Online ISBN: 978-3-642-00264-9
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