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Author:

Duan, Jianmin (Duan, Jianmin.) (Scholars:段建民) | Shi, Lixiao (Shi, Lixiao.) | Yao, Junqin (Yao, Junqin.) | Liu, Dan (Liu, Dan.) | Tian, Qi (Tian, Qi.)

Indexed by:

CPCI-S

Abstract:

In order to complete the task of vehicle's autonomous driving in structural road, it's necessary to detect obstacles. This paper proposed a method of obstacle detection, taking use of the four-line laser radar. This algorithm combined the improved DBSCAN with K-Means and overcame DBSCAN's defect that it couldn't divide obstacles with similar density. At the same time, this method can eliminate noise points effectively. Based on clustering, obstacle's information can be acquired, such as angle, distance and size, to achieve the task of obstacle detection. The algorithm is applied to obstacle detection in intelligent vehicle. The test proved that it is consistent and reliable, which complies with the requirement of intelligent vehicle's autonomous driving.

Keyword:

K-means Intelligent vehicle DBSCAN Laser radar Obstacle detection

Author Community:

  • [ 1 ] [Duan, Jianmin]Beijing Univ Technol, Dept Control Sci & Engn, Measurement Control Syst & Equipment Grp, Beijing 100022, CO, Peoples R China
  • [ 2 ] [Shi, Lixiao]Beijing Univ Technol, Dept Control Sci & Engn, Measurement Control Syst & Equipment Grp, Beijing 100022, CO, Peoples R China
  • [ 3 ] [Yao, Junqin]Beijing Univ Technol, Dept Control Sci & Engn, Measurement Control Syst & Equipment Grp, Beijing 100022, CO, Peoples R China
  • [ 4 ] [Liu, Dan]Beijing Univ Technol, Dept Control Sci & Engn, Measurement Control Syst & Equipment Grp, Beijing 100022, CO, Peoples R China
  • [ 5 ] [Tian, Qi]Beijing Univ Technol, Dept Control Sci & Engn, Measurement Control Syst & Equipment Grp, Beijing 100022, CO, Peoples R China

Reprint Author's Address:

  • 段建民

    [Duan, Jianmin]Beijing Univ Technol, Dept Control Sci & Engn, Measurement Control Syst & Equipment Grp, Beijing 100022, CO, Peoples R China

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Source :

2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO)

Year: 2013

Page: 2452-2457

Language: English

Cited Count:

WoS CC Cited Count: 5

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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