Terrain Mapping and Classification Using Support Vector Machines

被引：0

作者：

Hata, Alberto Yukinobu ^{[1
]}

Wolf, Denis Fernando ^{[1
]}

机构：

[1] Univ Sao Paulo, Mobile Robot Lab, Sao Carlos, SP, Brazil

来源：

2009 6TH LATIN AMERICAN ROBOTICS SYMPOSIUM | 2009年

关键词：

Environment mapping; navigation; SVM; LRF;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes a three-dimensional terrain mapping and classification technique to allow the operation of mobile robots in outdoor environments using laser range finders. We use Support Vector Machines to classify portions of mapped terrain into navigable, partially navigable and non-navigable. In order to detect safe places to robot traverse, our approach can be used to assist the robot navigation in unstructured lands. Experimental results obtained using real environments and robot show the efficiency of the presented methods.

引用

页码：20 / 25

页数：6

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