Abstract
Recently, various mechanisms have been
developed combining linkage mechanisms and wheels, especially,
the combination of passive linkage mechanisms and small wheels
is one of main research trends, because standard wheel type
mobile mechanisms have difficulties on rough terrain
movements. In our research, a 6-wheeled mobile robot employing
a passive linkage mechanism has been developed to enhance
maneuverability and achieved climbing capability over a 0.20[m]
height of bump. We designed a controller using neural network
for high energy efficiency. In this paper, we propose an
environment recognition system for the wheel type mobile robot
which consists of multiple classification analyses. We evaluate the
recognition performance by comparing Principle Component
Analyses (PCA), k-means and Self-Organizing Map (SOM).
