Automatic Floor Segmentation for Indoor Robot Navigation

摘要：

Indoor autonomous robots can perform desired task in indoor environments without continuous human guidance, so navigation is indispensable for them. In the state of the art of vision-based navigation, one or more cameras are usually installed on a robot. This has led to a larger workload to deal with the data collected by cameras and arises the problem of delay. In the paper, we propose a novel vision-based navigation framework for indoor autonomous robots in which the camera is fixed on the ceiling. Ia-the navigation scheme. a robot takes floor as their moving regions. So floor segmentation algorithm has to be designed to get floor regions in navigation images automatically. We adopted clustering analysis to implement automatic floor segmentation, and we also proposed a PCA based improved version of the algorithm to remove negative effect of shadow for segmented results.

关键词： YCbCr K-means clustering principal component analysis (PCA) floor segmentation color feature extraction

作者: Ma Ling Zhang Qigui Wang Jianming Liu Xiaoming Zhang Bo WangShengbei

作者单位: Department of Information and Communication Engineering Tianjin Polytechnic University, TJPU Tianjin College of Information Engineering Taiyuan University of Technology Taiyuan, China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 684-689

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）