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Journal of Bionic Engineering

, Volume 5, Supplement 1, pp 113–120 | Cite as

Environment Recognition System Based on Multiple Classification Analyses for Mobile Robots

  • Atsushi KandaEmail author
  • Masanori Sato
  • Kazuo Ishii
Article

Abstract

Various mechanisms have recently been developed that combine linkage mechanisms and wheels. In particular, the combination of passive linkage mechanisms and small wheels is a main research trend because standard wheeled mobile mechanisms find it difficult to move on rough terrain. In our previous research, a six-wheel mobile robot employing a passive linkage mechanism has been developed to enhance maneuverability and was able to climb over a 0.20 m bump and stairs. We designed a hybrid velocity and torque controller using a neural network since simple velocity controllers fail to climb up. In this paper, we propose an environment recognition system for a wheeled mobile robot that consists of multiple classification analyses to make the robot more adaptive to various environments by selecting a suitable system such as decision making, navigation and controller using the result of the environment recognition system. We evaluate the recognition performance in operation environments; slopes, bumps and stairs by comparing principle component, k-means and self-organizing map analyses.

Keywords

wheeled mobile robot neural network self-organizing map environment recognition 

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Copyright information

© Jilin University 2008

Authors and Affiliations

  1. 1.Department of Brain Inspired Science and EngineeringKyushu Institute of TechnologyKitakyushuJapan

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