本文選題：導(dǎo)購(gòu)機(jī)器人 + ROS�。� 參考：《西南科技大學(xué)》2017年碩士論文

【摘要】：隨著人類社會(huì)的快速發(fā)展,機(jī)器人技術(shù)正逐漸改變著人們的生活方式。針對(duì)由商場(chǎng)中商品數(shù)量的增多導(dǎo)致購(gòu)物者很難快速找到欲購(gòu)買商品的位置的難題,本課題研制了一種基于三輪全向?qū)з?gòu)機(jī)器人的自主定位與導(dǎo)航系統(tǒng),可以自主地引導(dǎo)購(gòu)物者到達(dá)商場(chǎng)中任意欲購(gòu)買商品位置。為了使系統(tǒng)具有良好的擴(kuò)展性及高代碼復(fù)用率,方便對(duì)導(dǎo)購(gòu)機(jī)器人進(jìn)行后續(xù)深入研究,本文選取了目前最通用的ROS(Robot Operating System)作為軟件開發(fā)平臺(tái),對(duì)導(dǎo)購(gòu)機(jī)器人關(guān)鍵技術(shù)展開研究。首先,針對(duì)粒子濾波定位中重采樣帶來的粒子匱乏問題,本文提出應(yīng)用粒子群聚散程度來動(dòng)態(tài)添加隨機(jī)粒子以減小定位誤差。同時(shí),通過加入KL距離對(duì)粒子集分布進(jìn)行近似,可以實(shí)時(shí)地、自適應(yīng)地改變用于狀態(tài)估計(jì)的粒子數(shù)以減輕系統(tǒng)計(jì)算量。其次,針對(duì)由商場(chǎng)人員較多、環(huán)境動(dòng)態(tài)性較大帶來的避障難度大的問題,本文把A-star與DWA結(jié)合起來應(yīng)用于導(dǎo)購(gòu)機(jī)器人的路徑規(guī)劃,提高其移動(dòng)靈活性。同時(shí),針對(duì)商場(chǎng)環(huán)境復(fù)雜性、碰撞風(fēng)險(xiǎn)大的情況,本文將激光掃描和深度圖像結(jié)合來精確感知環(huán)境,不僅具備二維激光掃描儀平面內(nèi)探測(cè)范圍廣、精度高、實(shí)時(shí)性好的特點(diǎn),而且兼有Kinect深度相機(jī)三維感知信息豐富的優(yōu)勢(shì)。實(shí)驗(yàn)證明該方法工作有效,能有效完成三維空間避碰。最后,以三輪全向?qū)з?gòu)機(jī)器人為實(shí)驗(yàn)平臺(tái),本文實(shí)現(xiàn)了前述的定位和路徑規(guī)劃方法。實(shí)驗(yàn)結(jié)果表明,這些方法可以安全無誤地幫助機(jī)器人完成自主定位與導(dǎo)航。
[Abstract]:With the rapid development of human society, robot technology is gradually changing people's way of life.In order to solve the problem that shoppers find it difficult to find the location of goods quickly due to the increase in the number of goods in the shopping mall, a kind of autonomous positioning and navigation system based on three-wheeled omnidirectional robot is developed in this paper.You can independently guide shoppers to the shopping mall where you want to buy goods.In order to make the system have good expansibility and high code reuse rate, and facilitate the further study of the purchase guide robot, this paper selects the most common ROS(Robot Operating system as the software development platform, and studies the key technology of the purchase guide robot.Firstly, aiming at the problem of particle scarcity caused by resampling in particle filter localization, this paper proposes a method to dynamically add random particles to reduce the location error by using particle swarm clustering.At the same time, by adding KL distance to approximate the distribution of particle sets, the number of particles used for state estimation can be changed in real time and adaptively to reduce the computational complexity of the system.Secondly, aiming at the difficulty of avoiding obstacles caused by more people in shopping malls and larger dynamic environment, this paper applies A-star and DWA to the path planning of purchase guide robot to improve its mobility.At the same time, aiming at the complex environment and high collision risk, this paper combines laser scanning and depth image to accurately perceive the environment, which not only has the characteristics of wide detection range, high accuracy and good real-time performance, but also has a wide range of detection in the plane of two-dimensional laser scanner.And also has the Kinect depth camera 3D perception information rich advantage.Experiments show that the method is effective and can effectively avoid collision in three-dimensional space.Finally, with the three-wheel omnidirectional robot as the experimental platform, this paper implements the above positioning and path planning methods.Experimental results show that these methods can safely and accurately help the robot to complete autonomous positioning and navigation.
【學(xué)位授予單位】：西南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP242

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