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基于多傳感器信息融合的智能車輛局部環(huán)境識
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Environment Recognition Based on the Data Fusion of LMS and Vision
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    為了對自主車輛在實時行駛中的駕駛避障給予指示并進行路徑規(guī)劃，提出并驗證了一種基于激光雷達深度信息以及圖像紋理信息的局部環(huán)境判別算法,；根據車輛的通過性指標對車輛進行動力性建模,，通過改進的Dempster-Shafer判據對識別結果進行融合,；并且輸出固定監(jiān)視區(qū)域內的通過性指數(shù)矩陣以指引自主車輛實時修正導向,。

    Abstract:

    In order to guide the UGV detection, a new method of local environment recognition based on the data fusion of LMS and vision were given and tested. Firstly the structure of LMS system and vision system has been modeled separately, and then the algorithm was showed to describe the data processing procedure. The grid method has been used to classify obstacle points and evaluate their cost. Considering the motor vehicle trafficability, an upgraded Dempster-Shafer criterion was used to revise the decision-making of driving. The trafficability was evaluated by reliability matrix. At last, the experiment has been done to validate the whole system. 

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張博,陳慧巖.基于多傳感器信息融合的智能車輛局部環(huán)境識[J].農業(yè)機械學報,2009,40(2):159-163. Environment Recognition Based on the Data Fusion of LMS and Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(2):159-163.

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