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基于自適應(yīng)導(dǎo)航參數(shù)的智能車輛視覺導(dǎo)航
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國家自然科學(xué)基金資助項(xiàng)目(51075112)和安徽科技學(xué)院人才引進(jìn)(穩(wěn)定)資助項(xiàng)目(ZRC2011302)


Navigation of Vision-guided Intelligent Vehicle Based on Adaptive Navigation Parameters
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    摘要:

    為提高導(dǎo)航路徑識(shí)別的魯棒性和實(shí)時(shí)性,,采用了分區(qū)閾值二值化,、噪聲點(diǎn)搜索及濾波等圖像處理方法,并對(duì)導(dǎo)航路徑進(jìn)行分區(qū)逐段識(shí)別,;在路徑跟蹤方面,,在獲取的導(dǎo)航路徑圖像中選取遠(yuǎn)端路徑和近端路徑,,以遠(yuǎn)端路徑和近端路徑的方位偏差量作為確定目標(biāo)路徑的依據(jù),使提取的導(dǎo)航參數(shù)能適應(yīng)導(dǎo)航路徑的變化,。根據(jù)四輪智能車輛模型進(jìn)行路徑跟蹤仿真計(jì)算,。在此基礎(chǔ)上,采用兩塊數(shù)字信號(hào)處理器,,對(duì)基于路徑導(dǎo)航的視覺智能車輛進(jìn)行了設(shè)計(jì)和試驗(yàn)驗(yàn)證,。試驗(yàn)結(jié)果表明采用該方法設(shè)計(jì)的智能車輛具有較好的路徑識(shí)別和跟蹤控制效果。

    Abstract:

    In order to obtain better robustness and real-time processing of path recognition, the binary segmentation image, noise searching and filtering procedures were employed. The whole path was classified into far part and near part, and the difference between the two parts was used as a threshold for selecting target road. So the navigating parameters were adapted to the changing path. Based on a model of four-wheel intelligent vehicle, a path tracking simulation was performed. Then, the navigation system based on path tracking was designed by using two digital signal processors. The experiments showed the accuracy and robustness of the system.

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李進(jìn),陳無畏.基于自適應(yīng)導(dǎo)航參數(shù)的智能車輛視覺導(dǎo)航[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2012,43(6):19-24,152. Li Jin, Chen Wuwei. Navigation of Vision-guided Intelligent Vehicle Based on Adaptive Navigation Parameters[J]. Transactions of the Chinese Society for Agricultural Machinery,2012,43(6):19-24,152.

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  • 在線發(fā)布日期: 2012-06-19
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