Hideaki Takeda's Publication
- K. Terada, K. Mochizuki, A. Ueno, H. Takeda,
T. Nishida, T. Nakamura, A. Ebina and H. Fujiwara: A Method for
Localization by Integration of Imprecise Vision and a Field Model, in
The Third Internatilnal Workshop on RoboCup, pp. 223–227 (1999).
In recent years, many researchers in AI and Robotics pay attention
to RoboCup, because robotic soccer games needs various techniques in AI and
Robotics, such as navigation, behavior generation, localization and
environment recognition. Localization is one of the important issues for
RoboCup. In this paper, we propose a method of robot's localization by
integrating vision and modeling of the environment. The environment model
that realizes the robotic soccer filed in the computer can produce an image
of robot's view at any location. In the environment model, the system can
search and appropriate location of which view image is similar to the view
image by the real robot. Our robot can estimate location form goal's height
and aspect ratio on the camera image. We search the most suitable position
with hill-climbing algorithm form the estimated location. We programmed this
method, and tested validity. The error range is reduced form 1m-50cm by
robot's estimation from 40cm-20cm by this method. This method is superior to
the other methods using dead reckoning or range sensor with map because it
does not depend on the field size on precision, and does not need walls as
landmark.
Hideaki Takeda (National Institute of Informatics)