THE RESEARCH OF OBSTACLE DETECTION BASED ON AK-MEANS CLUSTERING ALGPRITHM IN CROSS-COUNTRY

被引：0

作者：

Xu, Youchun ^{[1
]}

Cao, Jian ^{[1
]}

Jia, Peng ^{[1
,2
]}

Zhang, Zufeng ^{[1
]}

机构：

[1] Mil Transportat Univ, Tianjin 300161, Peoples R China

[2] Inst Chinese Elect Equipment Syst Engn Co, Beijing 100141, Peoples R China

来源：

2012 IEEE 2nd International Conference on Cloud Computing and Intelligent Systems (CCIS) Vols 1-3 | 2012年

关键词：

AK-mean; Cross-country; Obstacle detection; Laser radar;

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：

In order to obtain obstacle information in the cross-county environment for an unmanned ground vehicle (UGV), AK-means clustering algorithm is applied in four-layer laser radar data mining in this paper. The result of clustering serves as candidate obstacles. To overcome the false clustering due to vibration of UGV, weighted Euclidean distance is used to improve Davies-Bouldin Index (DBI). The experimental results show that the proposed obstacle detection algorithm is reliable and robust in low speed driving.

引用

页码：1196 / 1199

页数：4

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