Abstract
This paper presents a new method of building maps of workspace for autonomous mobile robots using self-organizing neural networks. By this method, the topological maps of the workspace can be self-organized from the relative distance data between a robot and walls on the workspace only using ultrasonic distance sensors. However, when the shape of the workspace is complicated, an unsuitable map with dead nodes or dead links may be generated. In this paper, we consider the cause of the problem, and we propose a new building maps algorithm which consists of two learning stages.
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References
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© 2000 Springer-Verlag London
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Hori, K., Hashimoto, Y., Wang, S., Tsuchiya, T. (2000). Building Maps of Workspace for Autonomous Mobile Robots Using Self-Organizing Neural Networks. In: Suzuki, Y., Ovaska, S., Furuhashi, T., Roy, R., Dote, Y. (eds) Soft Computing in Industrial Applications. Springer, London. https://doi.org/10.1007/978-1-4471-0509-1_16
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DOI: https://doi.org/10.1007/978-1-4471-0509-1_16
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1155-9
Online ISBN: 978-1-4471-0509-1
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