一种鲁棒的基于全向视觉的足球机器人自定位方法

A Robust Self-Localization Method Based on Omnidirectional Vision for Soccer Robots

针对RoboCup中型组机器人足球比赛环境高度动态的特点和现有定位方法的不足,提出了一种鲁棒的基于全向视觉的自定位方法.该方法结合使用粒子滤波定位和匹配优化定位,同时还设计了基于图像熵的摄像机参数自动调节算法以使全向视觉的输出能够适应光线条件的变化.实验结果表明,通过使用该方法,机器人能够在实时获得高精度自定位的同时实现可靠的全局定位,并对遮挡、光线条件变化等环境动态因素具有很强的鲁棒性.

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.