Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1007/3-540-45327-X_43 | RoboCup 2009 |
Keywords | Field | DocType |
camera image,error range,estimated location,view image,range sensor,environment model,imprecise vision,real robot,field model,appropriate location,robotics pay attention,environment recognition,aspect ratio,hill climbing,dead reckoning | Computer vision,Simulation,Computer science,Dead reckoning,Artificial intelligence,Camera image,Mobile robot navigation,Systems architecture,Robot,Landmark,Mobile robot,Robotics | Conference |
Volume | ISSN | ISBN |
1856 | 0302-9743 | 3-540-41043-0 |
Citations | PageRank | References |
1 | 0.47 | 7 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazunori Terada | 1 | 73 | 17.42 |
| Kouji Mochizuki | 2 | 1 | 0.47 |
| Atsushi Ueno | 3 | 1 | 0.47 |
| Hideaki Takeda | 4 | 87 | 36.35 |
| Toyoaki Nishida | 5 | 1097 | 196.19 |
| Takayuki Nakamura | 6 | 22 | 4.97 |
| Akihiro Ebina | 7 | 5 | 0.99 |
| Hiromitsu Fujiwara | 8 | 1 | 0.80 |