Separation of position and direction information of robots by a product model of self-organizing map and neural gas

✍ Scribed by Akira Date; Koji Kurata

• Publisher: John Wiley and Sons
• Year: 2005
• Tongue: English
• Weight: 549 KB
• Volume: 36
• Category: Article
• ISSN: 0882-1666
• DOI: 10.1002/scj.20349

✦ Synopsis

Abstract

This paper proposes a neural network model which receives visual inputs from a robot moving freely in a room, and extracts its position and direction information separately. The model has three‐dimensional structure in which two‐dimensional neural fields (unit planes) are arranged in a toroidal form. The learning algorithm takes a form of neural gas in each unit plane and self‐organizing map (SOM) in the toroidal direction. It is shown by computer simulation that position and view direction of the robot can be extracted from visual inputs, and the effectiveness of the learning algorithm is verified. © 2005 Wiley Periodicals, Inc. Syst Comp Jpn, 36(11): 1–11, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20349