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復(fù)雜環(huán)境下自動導(dǎo)引車路徑識別算法
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國家自然科學(xué)基金資助項目(50505045)、浙江省科技攻關(guān)重點(diǎn)項目(2006C21037)和浙江省自然科學(xué)基金資助項目（Y1110171）


Guidance Line Identification Algorithm for AGV in Complex Environment
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    摘要:

    為了快速準(zhǔn)確提取復(fù)雜環(huán)境下的自動導(dǎo)引車(AGV)引導(dǎo)路標(biāo)參數(shù),，提出一種基于先驗知識的直線識別算法,。根據(jù)視野和引導(dǎo)線結(jié)構(gòu)特征將全圖劃分為若干子區(qū)域,，確定子區(qū)域自適應(yīng)閾值,，利用前幀圖像中的直線參數(shù)信息選擇行列掃描方式,，剔除干擾點(diǎn)并獲得中線點(diǎn)集,，然后采用帶搜索角度限制和分區(qū)域非均勻采樣的改進(jìn)Hough變換得到直線參數(shù),，最后用交比定理對參數(shù)加以校正。試驗表明本算法能在不同光照,、反光,、陰影下對路徑進(jìn)行有效識別，具有較好魯棒性,，處理分辨率為576×768的圖像,，每幀平均用時不超過90 ms，滿足運(yùn)行需要,。

    Abstract:

    In order to quickly and accurately identify the guidance line in complex environment, a line recognition algorithm based on prior knowledge was proposed. Images were divided into several regions by field range and line characteristic. Both means of full image and region were used to make adaptive threshold of each region. Scanning mode was decided by information of previous image, then noises were filtered and intermediate points were acquired. An improved Hough transformation with search angle limitation and nonuniform sampling was applied to localize guidance line. Finally cross ratio theorem was used to calibrate the parameters. The experimental result showed the method was characterized by robustness and real-time, the average computing time was about 90ms for each image.

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蔡晉輝,才輝,張光新,周澤魁.復(fù)雜環(huán)境下自動導(dǎo)引車路徑識別算法[J].農(nóng)業(yè)機(jī)械學(xué)報,2011,42(10):20-24,89. Cai Jinhui, Cai Hui,Zhang Guangxin, Zhou Zekui. Guidance Line Identification Algorithm for AGV in Complex Environment[J]. Transactions of the Chinese Society for Agricultural Machinery,2011,42(10):20-24,89.

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