Scene Analysis for Mobile Robot Based on Multi-Sonar-Ranger Data

摘要：

The ability of cognition and recognition for complex environment is very important for a real autonomous robot. A new scene analysis method using Kernel Principal Component Analysis (PCA) for mobile robot based on multi-sonar-ranger data is put forward. The principle of classification by Principal Component Analysis (PCA), Kernel-PCA, and the BP neural network approach to extract the largest k eigenvectors are introduced briefly. Next PCA, Kernel-PCA and the BP neural network methods are applied in the corridor scene analysis and classification for the mobile robots based on sonar data.At last the experimental results using PCA, Kernel-PCA and the BP neural network are compared and such conclusions are drawn: in common corridor scene classification, the Kernel-PCA method has advantage over the ordinary PCA, and the BP Neural Network approach can also get satisfactory result.

关键词： Sonar PCA Kernel PCA mobile robot classification.

作者: Xiuqing Wang Zengguang Hou Yongqian Zhang Min Tan Anmin Zou Hongming Wang

作者单位: Key Laboratory of Complex Systems and Intelligence Science,Institute of Automation, The Chinese Acad Key Laboratory of Complex Systems and Intelligence Science,Institute of Automation, The Chinese Acad

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 365-369

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）