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Date of Publication:2011-01-01

Journal:数据采集与处理

Affiliation of Author(s):运载工程与力学学部

Issue:4

Page Number:442-446

ISSN No.:1004-9037

Abstract:Autonomous navigation in cross-country environments presents many new challenges including obstacle perception for unmanned ground vehicle. A new method suitable for recognizing obstacle is proposed. The first step is to build the sensor fusion system by using sensors such as CCD and ladar, then to extract five different types of features, including distance contrast, parallelogram rate, edge-shape-factor, gray texture and HSV value. The experiment formula is selected according to the types of obstacle and weight efficiency to calculate basic probability assignment (BPA). The subordinatien to each event in identification framework is obtained by using the fuzzy interpolation. It is supposed that the subordination is equal to correlation coefficient in the formula. Finally, dempster rules are used to integrate sensors information and the obstacle is recognized based on the D-S theory of evidence. The test results indicate that the resolution of BPA is correct, thus improving the validity and robustness of cross-country environment perception based on the new method.

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