Abstract
Environmental map building is an important premise of robot navigation, Self-Organizing Map (SOM) or Growing Self-Organizing Map (GSOM) can establish the topological map of the indoor environment through the environmental cognition. Aimed at the problem of traditional SOM containing error structure in constructing topological map while long time consuming of GSOM, this paper proposes a Prunable Self-Organizing Map (PSOM) algorithm which can prune wrong connections between neurons from the environmental structure, thus proving accurate topology while greatly reducing the implementation cost of the program compared to the Growing Self-Organizing Map. The proposed method (PSOM) is verified by experimental of environment map building based on physical indoor environment.
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Li, C., Ruan, Xg., Gu, K., Zhu, Xq. (2018). Construction of an Indoor Topological Map of a Robot Based on Prunable Self-Organizing Map. In: Zhai, G., Zhou, J., Yang, X. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2017. Communications in Computer and Information Science, vol 815. Springer, Singapore. https://doi.org/10.1007/978-981-10-8108-8_44
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DOI: https://doi.org/10.1007/978-981-10-8108-8_44
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