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Localization and obstacle avoidance in soccer competition of humanoid robot by gait and vision system

Part of: Robot Athletes and Entertainers

Published online by Cambridge University Press:  20 November 2019

Shu-Yin Chiang Open the ORCID record for Shu-Yin Chiang [Opens in a new window]  and
Jia-Huei Lu
Shu-Yin Chiang*
Affiliation:
Department of Information and Telecommunications Engineering, Ming Chuan University, 5 De Ming Road, Gui Shan District, Taoyuan City 333, Taiwan; e-mail: sychiang@mail.mcu.edu.tw
Jia-Huei Lu
Affiliation:
Department of Information and Telecommunications Engineering, Ming Chuan University, 5 De Ming Road, Gui Shan District, Taoyuan City 333, Taiwan; e-mail: sychiang@mail.mcu.edu.tw
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Abstract

In this study, we designed a localization and obstacle avoidance system for humanoid robots in the Federation of International Robot-soccer Association (FIRA) HuroCup united soccer competition event. The localization is implemented by using grid points, gait, and steps to determine the positions of each robot. To increase the localization accuracy and eliminate the accumulated distance errors resulting from step counting, the localization is augmented with image pattern matching using a system model. The system also enables the robot to determine the ball’s position on the field using a color model of the ball. Moreover, to avoid obstacles, the robots calculate the obstacle distance using data extracted from real-time images and determine a suitable direction for movement. With the integration of this accurate self-localization algorithm, ball identification scheme, and obstacle avoidance system, the robot team is capable of accomplishing the necessary tasks for a FIRA soccer game.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 34 , 2019 , e16
Copyright
© Cambridge University Press, 2019 

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