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 language | English |
|---|---|
| Title of host publication | Proceedings of the 32nd Chinese Control Conference, CCC 2013 |
| Publisher | IEEE Computer Society |
| Pages | 5722-5727 |
| Number of pages | 6 |
| ISBN (Print) | 9789881563835 |
| Publication status | Published - 18 Oct 2013 |
| Event | 32nd Chinese Control Conference, CCC 2013 - Xi'an, China Duration: 26 Jul 2013 → 28 Jul 2013 |
Publication series
| Name | Chinese Control Conference, CCC |
|---|---|
| ISSN (Print) | 1934-1768 |
| ISSN (Electronic) | 2161-2927 |
Conference
| Conference | 32nd Chinese Control Conference, CCC 2013 |
|---|---|
| Country/Territory | China |
| City | Xi'an |
| Period | 26/07/13 → 28/07/13 |
Keywords
- 3D Laser Ranger
- Feature Extraction
- HMM
- Machine Vision
- Terrain Classification
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Zuo, L., Wang, M., & Yang, Y. (2013). Complex terrain classification algorithm based on multi-sensors fusion. In Proceedings of the 32nd Chinese Control Conference, CCC 2013 (pp. 5722-5727). Article 6640439 (Chinese Control Conference, CCC). IEEE Computer Society.