A Robust Self-Localization Method Based on Omnidirectional Vision for Soccer Robots
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Abstract
According to the high dynamics of robot soccer competition in RoboCup Middle Size League and the deficiency of the current self-localization methods,a robust self-localization method based on omnidirectional vision is proposed.The method combines the particle filter localization with the matching optimization localization,and a camera parameter auto-adjusting algorithm based on image entropy is also proposed to adapt the output of omnidirectional vision to the dynamic lighting conditions.The experimental results show that global localization can be realized effectively with the proposed method while highly accurate self-localization is achieved in real-time,and robot's self-localization is robust to the highly dynamic environment with occlusion and varying lighting conditions.
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