Shih-Hung Chang1, Chih-Hsien Hsia2, Wei-Hsuan Chang1 and Jen-Shiun Chiang This email address is being protected from spambots. You need JavaScript enabled to view it.1
1Department of Electrical Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C. 2Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan 106, R.O.C.
Received: January 20, 2010 Accepted: December 14, 2010 Publication Date: December 1, 2011
Robot soccer game is one of the significant and interesting areas among most of the autonomous robotic researches. Following the humanoid soccer robot basic movement and strategy actions, the robot is operated in a dynamic and unpredictable contest environment and must recognize the position of itself in the field all the time. Therefore, the localization system of the soccer robot becomes the key technology to improve the performance. This work proposes efficient approaches for humanoid robot and uses one landmark to accomplish the self-localization. This localization mechanism integrates the information from the pan/tilt motors and a single camera on the robot head together with the artificial neural network technique to adaptively adjust the humanoid robot position. The neural network approach can improve the precision of the localization. The experimental results indicate that the average accuracy ratio is 88.5% under frame rate of 15 frames per second (fps), and the average error for the distance between the actual position and the measured position of the object is 6.68 cm.
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