Real time self-localization of omni-vision robot by pattern match system

Chiang, Shu‐Yin; Guo, Xingzhi; Hu, Hsien-Wen

doi:10.1109/aris.2014.6871525

Cited by 8 publications

(2 citation statements)

References 6 publications

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“…However, goalposts have not been available in the RoboCup since 2009 and are not available in the HuroCup. As the white lines provide information regarding the field, Chiang et al (2014) proposed a white-line pattern-matching localization method for a middle-sized robot soccer game.…”

Section: Introductionmentioning

confidence: 99%

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

Chiang

2019

The Knowledge Engineering Review

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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.

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Section: Introductionmentioning

confidence: 99%

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

Chiang

2019

The Knowledge Engineering Review

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“…In [47], the author presented a method for robot localization in a pre-defined work space, i.e., a soccer playground. In this method, the robot used an omni-directional vision sensor along with a gyroscopic sensor for localization.…”

Section: Omni-vision Robot Localization Using Pattern Match Systemmentioning

confidence: 99%

Position Estimation of Mobile Robots Using Omni-Directional Cameras

Fouad¹

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Mobile robots are prospected to significantly improve the efficiency and productivity of individuals. However, to fulfil their required tasks, they must be able to efficiently manoeuvre in their surrounding environments. This requirement necessitates that these robots posses the ability to acquire their current position and orientation within their work space. To acquire this information, mobile robots need precise and reliable perception techniques. Different perception methods has been described in Before beginning, I am extremely grateful to Allah for allowing me to reach this point in pursuing my goals. I am also extremely thankful for my supervisors Professor Jie Liu and Professor Jurek Sasiadek for their continuous support and encouragement along the Masters' journey. I am also thankful for my colleagues in the research lab for their encouragement and insightful suggestions for improving this work.

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