| Full text | |
| Author(s): |
Total Authors: 2
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| Affiliation: | [1] Univ Sao Paulo, Inst Math & Comp Sci, Sao Carlos, SP - Brazil
Total Affiliations: 1
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| Document type: | Journal article |
| Source: | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS; v. 62, n. 3-4, p. 527-546, JUN 2011. |
| Web of Science Citations: | 13 |
| Abstract | |
Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach. (AU) | |
| FAPESP's process: | 08/57870-9 - Critical Embedded Systems Institute |
| Grantee: | Jose Carlos Maldonado |
| Support Opportunities: | Research Projects - Thematic Grants |