【摘要】：隨著全球人口老齡化問(wèn)題的出現(xiàn),為了提高老人的生活質(zhì)量,人們對(duì)服務(wù)機(jī)器人的需求與日俱增。目前,面向家庭的服務(wù)機(jī)器人的研究與開(kāi)發(fā)已經(jīng)得到了廣泛的關(guān)注,家庭工作中的重復(fù)性工作或 苦力工作‖越來(lái)越多的由服務(wù)機(jī)器人承擔(dān)。服務(wù)機(jī)器人只有清楚自己的即時(shí)位置,以及如何從即時(shí)位置到達(dá)目標(biāo)位置后,才能夠有效地把特定的任務(wù)順利完成�？梢�(jiàn),自定位是服務(wù)機(jī)器人完成路徑規(guī)劃、自主導(dǎo)航等行為的基礎(chǔ),是移動(dòng)機(jī)器人自主完成任務(wù)的前提。本文針對(duì)室內(nèi)結(jié)構(gòu)化環(huán)境,服務(wù)機(jī)器人自主定位等關(guān)鍵技術(shù)進(jìn)行深入研究,構(gòu)建了一種基于Kinect深度視覺(jué)傳感器,人工信標(biāo)的室內(nèi)定位系統(tǒng),對(duì)傳統(tǒng)三邊定位算法進(jìn)行了改進(jìn)。從而提高了機(jī)器人在室內(nèi)結(jié)構(gòu)化環(huán)境中的自主定位能力。本論文的主要內(nèi)容如下:本論文首先綜述了服務(wù)機(jī)器人國(guó)內(nèi)外研究及應(yīng)用現(xiàn)狀,對(duì)服務(wù)機(jī)器人自定位技術(shù)進(jìn)行了分析和研究,并闡述了服務(wù)機(jī)器人自定位的意義。其次,詳細(xì)闡述了服務(wù)機(jī)器人硬件結(jié)構(gòu)、Kinect深度視覺(jué)傳感器的相關(guān)基本知識(shí)。同時(shí)構(gòu)建了服務(wù)機(jī)器人坐標(biāo)系模型、運(yùn)動(dòng)學(xué)模型。再次,針對(duì)傳統(tǒng)邊緣檢測(cè)算法測(cè)量精度低和范圍有限的不足,提出了基于Sobel算子的改進(jìn)算法。同時(shí),深入研究了Kinect視覺(jué)傳感器測(cè)距技術(shù)和工作原理,使用Kinect深度視覺(jué)傳感器進(jìn)行了測(cè)距實(shí)驗(yàn)。實(shí)驗(yàn)結(jié)果驗(yàn)證了其測(cè)量的準(zhǔn)確度。然后,開(kāi)展了室內(nèi)結(jié)構(gòu)化環(huán)境下服務(wù)機(jī)器人圖像配準(zhǔn)方法研究,指出了信息熵配準(zhǔn)方法、互信息配準(zhǔn)方法各自的不足之處。應(yīng)用邊緣特征和互信息的圖像配準(zhǔn)方法,仿真實(shí)驗(yàn)表明,所提出的方法能夠在室內(nèi)結(jié)構(gòu)化環(huán)境下配準(zhǔn)人工信標(biāo)。最后,對(duì)信標(biāo)定位與視覺(jué)定位做了深入的研究。構(gòu)建了基于Kinect深度視覺(jué)傳感器和人工信標(biāo)的室內(nèi)定位系統(tǒng),針對(duì)經(jīng)典三邊定位算法中容易出現(xiàn)的問(wèn)題進(jìn)行了改進(jìn)與完善。將改進(jìn)算法運(yùn)用到構(gòu)建的定位系統(tǒng)上,通過(guò)Matlab仿真實(shí)驗(yàn),驗(yàn)證其自定位的可行性。
[Abstract]:With the emergence of the global aging population, in order to improve the quality of life of the elderly, the demand for service robots is increasing. At present, the research and development of home oriented service robot has been paid more and more attention. More and more repetitive work or hard work in home work are undertaken by service robot. Only when the service robot knows its immediate position and how to get to the target position from the immediate position can it effectively complete the specific task successfully. It can be seen that self-localization is the basis of the behavior of path planning and autonomous navigation of the service robot and the premise of the autonomous completion of the task of the mobile robot. In this paper, the key technologies of indoor structured environment and autonomous localization of service robot are studied in depth. An indoor positioning system based on Kinect depth vision sensor and artificial beacon is constructed, and the traditional triangulation algorithm is improved. Thus, the autonomous positioning ability of robot in indoor structured environment is improved. The main contents of this thesis are as follows: firstly, this paper summarizes the research and application of service robot at home and abroad, analyzes and studies the self-localization technology of service robot, and expounds the significance of self-localization of service robot. Secondly, the hardware structure of service robot and the basic knowledge of Kinect depth vision sensor are described in detail. At the same time, the coordinate system model and kinematics model of service robot are constructed. Thirdly, an improved algorithm based on Sobel operator is proposed to solve the problem of low accuracy and limited range of traditional edge detection algorithms. At the same time, the ranging technology and working principle of Kinect vision sensor are deeply studied, and the ranging experiment with Kinect depth vision sensor is carried out. The experimental results verify the accuracy of the measurement. Then, research on image registration method of service robot in indoor structured environment is carried out, and the shortcomings of information entropy registration method and mutual information registration method are pointed out. The method of image registration based on edge features and mutual information is used. The simulation results show that the proposed method can match artificial beacons in an indoor structured environment. Finally, the beacons location and visual positioning are deeply studied. The indoor positioning system based on Kinect depth vision sensor and artificial beacon is constructed, and the problems in the classical trilateral localization algorithm are improved and improved. The improved algorithm is applied to the constructed localization system, and the feasibility of the self-localization is verified by Matlab simulation.
【學(xué)位授予單位】：沈陽(yáng)建筑大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41;TP242

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本文編號(hào)：2304942