B. Fritzke, “Growing Cell Structures—A Self-Organizing Network for Unsupervised and Supervised Learning,” Neural Network, Vol. 7, No. 9, 1994, pp. 1411-1460. doi:10.1016/0893-6080(94)90091-4

has been cited by the following article:

• TITLE: A New Dynamic Self-Organizing Method for Mobile Robot Environment Mapping

  AUTHORS: Xiaogang Ruan, Yuanyuan Gao, Hongjun Song, Jing Chen

  KEYWORDS: Mobile Robot, Environment Mapping, Growing-Threshold Tuning, Self-Organizing

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.3 No.4, November 29, 2011

  ABSTRACT: To solve the mapping problem for the mobile robots in the unknown environment, a dynamic growing self-organizing map with growing-threshold tuning automatically algorithm (DGSOMGT) based on Self-organizing Map is proposed. It introduces a value of spread factor to describe the changing process of the growing threshold dynamically. The method realizes the network structure growing by training through mobile robot movement constantly in the unknown environment. The proposed algorithm is based on self-organizing map and can adjust the growing-threshold value by the number of network neurons increasing. It avoids tuning the parameters repeatedly by human. The experimental results show that the proposed method detects the complex environment quickly, effectively and correctly. The robot can realize environment mapping automatically. Compared with the other methods the proposed mapping strategy has better topological properties and time property.