NDLI: Efficient neural network approach of self-localization for humanoid robot

Content Provider	IEEE Xplore Digital Library
Author	Shih-Hung Chang Wei-Hsuan Chang Chih-Hsien Hsia Fun Ye Jen-Shiun Chiang
Copyright Year	2009
Description	Author affiliation: Department of Electrical Engineering, Tamkang University, Taipei, Taiwan (Shih-Hung Chang; Wei-Hsuan Chang; Chih-Hsien Hsia; Fun Ye; Jen-Shiun Chiang)
Abstract	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 6.68cm.
Starting Page	149
Ending Page	154
File Size	7772139
Page Count	6
File Format	PDF
ISBN	9781424452279
DOI	10.1109/JCPC.2009.5420197
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-03
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems Self-Localization Accuracy Ration Natural languages Humanoid robots Humans Humanoid Soccer Robot Delay Loudspeakers Computer science Neural Network Neural networks Precision Broadcasting Speech
Content Type	Text
Resource Type	Article

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