【摘要】：隨著科技的快速發(fā)展,在一些生產(chǎn)領(lǐng)域和科研場所中存在高風險、高強度、高難度的工作環(huán)境,隨之出現(xiàn)了替代人類在這些環(huán)境中工作的機器人,而樓梯狀道路可能是機器人完成工作中通過的路徑,這就使得機器人在該路徑下要具有一定的檢測識別能力�；谝陨媳尘�,本文通過單目視覺傳感器獲取樓梯圖像信息,將樓梯邊緣線作為機器人可行駛的邊界,輔以相關(guān)的處理算法,進一步實現(xiàn)樓梯邊緣檢測與距離信息定位,為機器人的下一步路徑規(guī)劃提供一定條件。首先,針對樓梯圖像在不同情況下紋理特征不同的特點,對比研究了兩種特征分析方法:灰度差分統(tǒng)計法和灰度共生矩陣法,分別對上升和下降樓梯圖像中的特征進行分析,通過兩種方法對比,進而達到了區(qū)分上升下降樓梯圖像的目的。其次,針對傳統(tǒng)圖像邊緣檢測方法中出現(xiàn)噪聲、邊緣定位不精確等缺點,本文結(jié)合小波變換和形態(tài)學的優(yōu)點,提出了一種基于多方向小波變換和形態(tài)學融合的邊緣檢測算法,并對于不同環(huán)境下樓梯圖像進行了實驗,對比分析了該算法在不同環(huán)境下的適應(yīng)性。然后,在樓梯圖像邊緣檢測的基礎(chǔ)上,利用投影變換建立攝像機與目標點的幾何模型,在距離信息定位時,本文按照目標點在攝像機視野范圍內(nèi)的位置不同,將距離信息定位算法分成三種情況,按照目標點在成像平面坐標系中所在位置選擇其對應(yīng)計算公式,進一步實現(xiàn)樓梯邊緣距離信息定位。對于計算中需要的攝像機內(nèi)參數(shù),使用了攝像機標定法中的張氏標定法進行標定。通過實驗結(jié)果表明,本文提出的檢測算法能夠有效的實現(xiàn)樓梯圖像的檢測,提出的距離定位算法簡單高效,測量誤差小,為機器人下一步的運行提供有利的條件。
[Abstract]:With the rapid development of science and technology, there are high-risk, high-intensity, high-difficulty working environment in some fields of production and scientific research, along with the emergence of robots that replace human beings working in these environments. The staircase road may be the path through which the robot completes its work, which makes the robot have certain detection and recognition ability under this path. Based on the above background, this paper obtains the stair image information by monocular vision sensor, takes the stair edge line as the driving boundary of the robot, and uses the related processing algorithm to further realize the stair edge detection and the location of distance information. It provides some conditions for the next step path planning of the robot. Firstly, according to the different texture features of stair images under different conditions, two feature analysis methods, gray difference statistical method and gray level co-occurrence matrix method, are compared and studied to analyze the features of ascending and descending stair images, respectively. Through the comparison of the two methods, the purpose of distinguishing the ascending and descending staircase images is achieved. Secondly, aiming at the disadvantages of traditional image edge detection methods, such as noise and imprecise edge location, a new edge detection algorithm based on multi-direction wavelet transform and morphology fusion is proposed in this paper, which combines the advantages of wavelet transform and morphology. The experiment of stair image in different environment is carried out, and the adaptability of the algorithm in different environment is compared and analyzed. Then, on the basis of edge detection of stair image, the geometric model of camera and target point is established by using projection transformation. When the distance information is located, the position of target point in the field of view of camera is different according to the position of target point in the field of view of camera. The distance information location algorithm is divided into three cases. According to the location of the target point in the imaging plane coordinate system, the corresponding calculation formula is selected to further realize the stair edge distance information location. The camera calibration method is used to calibrate the internal parameters of the camera. The experimental results show that the detection algorithm proposed in this paper can effectively realize the detection of stair images, and the proposed range location algorithm is simple and efficient, and the measurement error is small, which provides favorable conditions for the next step of operation of the robot.
【學位授予單位】：西安科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

【參考文獻】

相關(guān)期刊論文 前10條

1 周茂林;;機器視覺智能檢測系統(tǒng)的研究[J];自動化應(yīng)用;2016年11期

2 邵校;陶建武;;基于單目視覺的靜止目標定位方法[J];光子學報;2016年10期

3 譚媛;黃輝先;徐建閩;陳任;;基于改進Sobel算子的遙感圖像道路邊緣檢測方法[J];國土資源遙感;2016年03期

4 黃志鴻;毛建旭;王耀南;周顯恩;歷艷琨;劉學兵;;基于機器視覺的啤酒瓶口缺陷檢測分類方法研究[J];電子測量與儀器學報;2016年06期

5 高峰;郭為忠;;中國機器人的發(fā)展戰(zhàn)略思考[J];機械工程學報;2016年07期

6 陳凱;王舒憬;;基于機器視覺的圖像邊緣檢測算法的優(yōu)化研究[J];工業(yè)控制計算機;2015年11期

7 陳英;;機器視覺檢測技術(shù)在工業(yè)檢測中的應(yīng)用[J];電子測試;2015年18期

8 王國彪;陳殿生;陳科位;張自強;;仿生機器人研究現(xiàn)狀與發(fā)展趨勢[J];機械工程學報;2015年13期

9 遲德霞;王洋;寧立群;衣娟;;張正友法的攝像機標定試驗[J];中國農(nóng)機化學報;2015年02期

10 葛杰;曹晨晨;李光;;基于機器視覺的圖像形狀特征提取方法研究進展[J];包裝學報;2015年01期

相關(guān)博士學位論文 前1條

1 磨少清;邊緣檢測及其評價方法的研究[D];天津大學;2011年

相關(guān)碩士學位論文 前4條

1 王田田;基于小波變換的圖像邊緣檢測[D];北京理工大學;2015年

2 姚怡;可上樓梯的智能機器人設(shè)計與實現(xiàn)[D];北京郵電大學;2013年

3 王婷婷;基于單目視覺的室內(nèi)目標定位技術(shù)研究[D];天津大學;2012年

4 步亞東;圖像紋理特征提取的研究[D];山東師范大學;2012年

，

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