【摘要】：近年來(lái),隨著生活水平提高和醫(yī)療衛(wèi)生技術(shù)的不斷發(fā)展,殘障和老年人士的生活質(zhì)量受到了更多的關(guān)注,智能移動(dòng)機(jī)器人的出現(xiàn)方便了他們的出行,成為了當(dāng)前輔助器械醫(yī)療領(lǐng)域一個(gè)新研究熱點(diǎn)。其中對(duì)于肢體殘障人士,基于頭部姿態(tài)的人機(jī)交互方式作為一個(gè)新的選擇,受到了許多消費(fèi)者和國(guó)內(nèi)外科研人員的青睞,具有較高的市場(chǎng)價(jià)值與研究?jī)r(jià)值。本文在頭部姿態(tài)識(shí)別研究的基礎(chǔ)上,將頭姿識(shí)別應(yīng)用于移動(dòng)服務(wù)機(jī)器人交互系統(tǒng),實(shí)現(xiàn)了利用頭部轉(zhuǎn)動(dòng)對(duì)移動(dòng)服務(wù)機(jī)器人的運(yùn)動(dòng)控制。主要研究成果如下:(1)頭部姿態(tài)識(shí)別是整個(gè)人機(jī)交互系統(tǒng)的基礎(chǔ),本文依據(jù)現(xiàn)有頭部姿態(tài)研究方法,利用機(jī)器視覺(jué)算法對(duì)頭部深度圖像進(jìn)行識(shí)別。本文使用Kinect深度傳感器采集頭部深度圖像,由于原始深度圖像存在噪聲孔洞等缺陷,在進(jìn)行識(shí)別時(shí)會(huì)存在諸多干擾,通過(guò)中值濾波算法和形態(tài)學(xué)濾波對(duì)原始深度圖像進(jìn)行預(yù)處理,方便后續(xù)的頭姿識(shí)別。(2)根據(jù)當(dāng)前國(guó)內(nèi)外研究現(xiàn)狀,利用隨機(jī)森林和ICP算法對(duì)頭部姿態(tài)進(jìn)行計(jì)算,在分別實(shí)現(xiàn)兩種算法后,分析兩種算法各自在在精度與實(shí)時(shí)性方面的局限性。本文提出隨機(jī)森林結(jié)合ICP算法的思想,利用隨機(jī)森林算法作為ICP算法的粗配準(zhǔn),減少I(mǎi)CP算法在精配準(zhǔn)階段的迭代次數(shù)。兩種算法互補(bǔ)對(duì)方的缺陷,使得頭姿計(jì)算具備了實(shí)時(shí)性和精確性。(3)頭部姿態(tài)與移動(dòng)機(jī)器人運(yùn)動(dòng)狀態(tài)之間的映射關(guān)系是人機(jī)交互系統(tǒng)的橋梁,本文提出頭部朝向向量模擬操縱搖桿的控制方式,該方式符合人的自然交互方式,并通過(guò)實(shí)驗(yàn)驗(yàn)證具備良好的控制效果。根據(jù)以上分析開(kāi)發(fā)基于頭部姿態(tài)識(shí)別的智能移動(dòng)服務(wù)機(jī)器人交互系統(tǒng),以Kinect為圖像采集裝置,PC為計(jì)算控制核心,移動(dòng)服務(wù)機(jī)器人為應(yīng)用平臺(tái),實(shí)現(xiàn)了整個(gè)人機(jī)交互系統(tǒng)。
[Abstract]:In recent years, with the improvement of living standards and the continuous development of medical and health technology, more attention has been paid to the quality of life of the disabled and the elderly, and the emergence of intelligent mobile robots has facilitated their travel. It has become a new research hotspot in the medical field of auxiliary devices. As a new choice, the human-computer interaction based on head posture is favored by many consumers and researchers at home and abroad, and has high market value and research value. Based on the research of head attitude recognition, this paper applies the head attitude recognition to the mobile service robot interactive system, and realizes the motion control of the mobile service robot by using the head rotation. The main research results are as follows: (1) head attitude recognition is the basis of the whole human-computer interaction system. According to the existing head attitude research methods, this paper uses machine vision algorithm to recognize the head depth image. In this paper, the Kinect depth sensor is used to collect the head depth image. Due to the defects of the original depth image, such as noise holes, there will be a lot of interference in the recognition. The median filter algorithm and morphological filter are used to preprocess the original depth image to facilitate the subsequent head-pose recognition. (2) according to the current research situation at home and abroad, the head attitude is calculated by using stochastic forest and ICP algorithm. After the two algorithms are implemented, the limitations of the two algorithms in accuracy and real time are analyzed. In this paper, the idea of combining stochastic forest with ICP algorithm is presented. The random forest algorithm is used as the rough registration of ICP algorithm, and the iterations of ICP algorithm in the stage of fine registration are reduced. The two algorithms complement each other's defects, which makes the head-pose calculation real-time and accurate. (3) the mapping relationship between the head attitude and the moving state of the mobile robot is the bridge of the human-computer interaction system. In this paper, a control method of steering rocker with head orientation vector simulation is proposed, which is in line with the natural interaction mode of human beings, and is proved to have a good control effect by experiments. Based on the above analysis, an intelligent mobile service robot interaction system based on head attitude recognition is developed. The whole human-computer interaction system is realized with Kinect as the image acquisition device, PC as the computing control core and mobile service robot as the application platform.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TP242

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 張琳;馬瑞卿;史國(guó)棟;相里康;;基于操作手柄新模型的電動(dòng)輪椅運(yùn)動(dòng)控制系統(tǒng)[J];微特電機(jī);2012年07期

2 董力賡;陶霖密;徐光yP;;基于二階梯度朝向直方圖特征的頭部姿態(tài)估計(jì)[J];清華大學(xué)學(xué)報(bào)(自然科學(xué)版);2011年01期

3 馬丙鵬;山世光;陳熙霖;高文;;一種基于圖像表觀的魯棒姿態(tài)估計(jì)方法[J];軟件學(xué)報(bào);2009年06期

4 原魁;;智能輪椅的研究現(xiàn)狀與趨勢(shì)[J];中國(guó)醫(yī)療器械信息;2009年01期

5 蔡自興;智能控制及移動(dòng)機(jī)器人研究進(jìn)展[J];中南大學(xué)學(xué)報(bào)(自然科學(xué)版);2005年05期

6 董士海;人機(jī)交互的進(jìn)展及面臨的挑戰(zhàn)[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2004年01期

，

本文編號(hào)：2295460