Complex terrain classification algorithm based on multi-sensors fusion

Liang Zuo, Meiling Wang, Yi Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Terrain detection under complex environment is important to environment perception for autonomous vehicle. This paper presents a terrain classification method based on multi-sensors data fusion. Raw data received from 3D laser ranger and camera is applied to get the feature of terrain firstly. Then the driving space is divided into stereo unit and each unit includes some inherent feature characteristics. Hidden markov model describe the structure of the driving space and model parameters are trained by Baum-Welch algorithm. Experiment results show that the method can classify the complex terrain effectively.

Original languageEnglish
Title of host publicationProceedings of the 32nd Chinese Control Conference, CCC 2013
PublisherIEEE Computer Society
Pages5722-5727
Number of pages6
ISBN (Print)9789881563835
Publication statusPublished - 18 Oct 2013
Event32nd Chinese Control Conference, CCC 2013 - Xi'an, China
Duration: 26 Jul 201328 Jul 2013

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference32nd Chinese Control Conference, CCC 2013
Country/TerritoryChina
CityXi'an
Period26/07/1328/07/13

Keywords

  • 3D Laser Ranger
  • Feature Extraction
  • HMM
  • Machine Vision
  • Terrain Classification

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