摘要
在机器人足球中,机器人周围的环境信息被颜色特殊化。在对基于颜色阈值分割的分析基础上,针对不同光线的情况下提出了改进的颜色阈值分割法,实现了全维视觉和前向单目视觉对场上不同颜色目标的识别。在此基础上实现了前项单目视觉和全维视觉的目标定位,利用Kalman滤波算法,实现二者的信息融合,从而实现更准确的目标定位信息。实验结果表明基于此算法可以弥补中远距离的目标信息的准确度,证明本算法是可行且有效的。
In the robot soccer system,the environmental information around the robot is characterized in colors.On the analysis of the color threshold segmentation,an improved algorithm practicable in different color environments is proposed to realize the identification of objects in different colors in the field through omni-direction vision and front monocular vision,by the use of which,the robot’s object location through the two visions can be realized and then a more accurate object location can be achieved by combining the information from the two visions through Kalman filter algorithm.Experimental results prove the feasibility and validity of this algorithm which improves the accuracy of medium-and-long-distance object location.
出处
《工程图学学报》
CSCD
北大核心
2011年第3期6-12,共7页
Journal of Engineering Graphics
基金
上海市机械自动化及机器人重点实验室开放课题(Z0802)
国家自然科学基金资助项目(60705015)
安徽省自然科学基金资助项目(070412064)
关键词
数字图像处理
卡尔曼滤波
定位
颜色阈值
digital image processing
Kalman filter
localization
color threshold