CVGIP: Image Understanding
RoboCup-98: Robot Soccer World Cup II
The RoboCup-NAIST: A Cheap Multisensor-Based Mobile Robot with Visual Learning Capability
RoboCup-98: Robot Soccer World Cup II
Techniques for Obtaining Robust, Real-Time, Colour-Based Vision for Robotics
RoboCup-99: Robot Soccer World Cup III
| Hi-index | 0.00 |
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 from goal's height and aspect ratio on the camera image. We search the most suitable position with hill-climbing algorithm from the estimated location. We programmed this method, and tested validity. The error range is reduced from 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.