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JACIII Vol.11 No.8 pp. 937-945
doi: 10.20965/jaciii.2007.p0937
(2007)

Paper:

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Hardware Feedback Self-Organizing Map and its Application to Mobile Robot Location Identification

Hiroomi Hikawa*, Kazutoshi Harada*, and Takenori Hirabayashi**

* Dept. of Computer Science and Intelligent Systems, Oita University, Oita 870-1192, Japan

** Shinko Electric Co., Ltd., Minato-ku, Tokyo 105-8564, Japan

Received:
March 15, 2007
Accepted:
May 23, 2007
Published:
October 20, 2007
Creative Commons License
Keywords:
hardware, feedback SOM, mobile robot, location identification, FPGA
Abstract
We propose new hardware architecture for the self-organizing map (SOM) and feedback SOM (FSOM). Due to the parallel structure in the SOM and FSOM algorithm, customized hardware considerably speeds-up processing. Proposed hardware FSOM identifies the location of a mobile robot from a sequence of direction data. The FSOM is self-trained to cluster data to identify where the robot is. The proposed FSOM design is described in C and VHDL, and its performance is tested by simulation using actual sensor data from an experimental mobile robot. Results show that the hardware FSOM succeeds in self-learning to find the robot’s location. The hardware FSOM is estimated to process 6,992 million weight-vector elements per second.
Cite this article as:
H. Hikawa, K. Harada, and T. Hirabayashi, “Hardware Feedback Self-Organizing Map and its Application to Mobile Robot Location Identification,” J. Adv. Comput. Intell. Intell. Inform., Vol.11 No.8, pp. 937-945, 2007.
Data files:
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Last updated on Oct. 11, 2024