發(fā)布時(shí)間：2018-03-29 12:10

  本文選題：全方位移動(dòng)機(jī)器人　切入點(diǎn)：語(yǔ)義拓?fù)涞貓D　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：21世紀(jì)以來(lái),中國(guó)逐漸步入老齡化社會(huì),出現(xiàn)“空巢老人”、老人無(wú)人陪護(hù)等社會(huì)問(wèn)題。為家庭服務(wù)機(jī)器人行業(yè)提出巨大的市場(chǎng)需求,與此同時(shí)也對(duì)機(jī)器人提出了巨大的挑戰(zhàn)。室內(nèi)環(huán)境移動(dòng)作業(yè)一直以來(lái)都是移動(dòng)機(jī)器人研究的重點(diǎn)問(wèn)題。由于機(jī)器人對(duì)于環(huán)境的理解局限于數(shù)字坐標(biāo)信息,而人對(duì)于環(huán)境的理解處于語(yǔ)義區(qū)域?qū)用?因此語(yǔ)義地圖構(gòu)建及語(yǔ)義導(dǎo)航成為移動(dòng)機(jī)器人領(lǐng)域的研究熱點(diǎn)。室內(nèi)環(huán)境屬于動(dòng)態(tài)環(huán)境,因此動(dòng)態(tài)環(huán)境導(dǎo)航也是一直以來(lái)研究的焦點(diǎn)。首先,設(shè)計(jì)基于Mecanum輪的全方位移動(dòng)機(jī)器人系統(tǒng)。針對(duì)室內(nèi)環(huán)境狹窄通過(guò)性差的特點(diǎn),設(shè)計(jì)基于Mecanum輪的機(jī)器人構(gòu)型,其中獨(dú)立懸掛結(jié)構(gòu)可增強(qiáng)機(jī)器人不平路面通過(guò)性及避免打滑;設(shè)計(jì)具有良好可替換性的伺服驅(qū)動(dòng)模塊,為機(jī)器人運(yùn)動(dòng)提供動(dòng)力;通過(guò)激光和視覺(jué)傳感器,建立立體的環(huán)境感知模型;軟件系統(tǒng)基于ROS操作系統(tǒng),可實(shí)現(xiàn)節(jié)點(diǎn)的弱耦合、多線程運(yùn)行,提高程序運(yùn)行效率。然后,建立機(jī)器人系統(tǒng)模型及環(huán)境地圖模型。針對(duì)本文全方位移動(dòng)機(jī)器人構(gòu)型開(kāi)展機(jī)器人運(yùn)動(dòng)控制以及位姿估計(jì)工作,分別建立運(yùn)動(dòng)控制模型和里程計(jì)模型;針對(duì)本文的主要傳感器激光傳感器進(jìn)行建模修正及坐標(biāo)系變換;面向語(yǔ)義導(dǎo)航需求,分別構(gòu)建語(yǔ)義拓?fù)鋵拥貓D和2D柵格層地圖。其次,研究了機(jī)器人定位及語(yǔ)義導(dǎo)航問(wèn)題。針對(duì)機(jī)器人定位,采用語(yǔ)義約束對(duì)AMCL定位算法的粒子分布進(jìn)行指導(dǎo),以此來(lái)加快機(jī)器人定位收斂速度,并減少誤匹配現(xiàn)象;語(yǔ)義拓?fù)鋵勇窂揭?guī)劃采用基于連通區(qū)域的搜索方法,可以加快搜索的速度,并且增強(qiáng)機(jī)器人的狹窄環(huán)境通過(guò)性;基于行人預(yù)測(cè)模型,采用基于A*的二次規(guī)劃方法進(jìn)行動(dòng)態(tài)環(huán)境機(jī)器人局部路徑規(guī)劃。最后,搭建基于Mecanum輪全方位移動(dòng)機(jī)器人實(shí)驗(yàn)平臺(tái),分別就機(jī)器人工作穩(wěn)定性、機(jī)器人室內(nèi)環(huán)境定位、機(jī)器人語(yǔ)義導(dǎo)航和動(dòng)態(tài)環(huán)境導(dǎo)航開(kāi)展實(shí)驗(yàn)研究,驗(yàn)證實(shí)驗(yàn)平臺(tái)的工作可靠性和上述算法的可行性。
[Abstract]:Since the 21st century, China has gradually stepped into an aging society, with social problems such as "empty nest old people" and the elderly being left unattended. It has put forward a huge market demand for the family service robot industry. At the same time, it also poses a great challenge to the robot. Indoor environment mobile operation has always been the focus of mobile robot research. Because the robot's understanding of the environment is limited to the digital coordinate information, Human understanding of the environment is at the level of semantic region, so semantic map construction and semantic navigation become the research hotspot in the field of mobile robot. Indoor environment belongs to dynamic environment. Therefore, dynamic environment navigation has always been the focus of research. Firstly, an omni-directional mobile robot system based on Mecanum wheel is designed. Aiming at the characteristics of narrow indoor environment, the robot configuration based on Mecanum wheel is designed. Among them, independent suspension structure can enhance the mobility of robot uneven road surface and avoid skid; design servo drive module with good substitutability to provide power for robot motion; through laser and vision sensor, The software system is based on ROS operating system, which can realize the weak coupling of nodes, multi-thread running, and improve the efficiency of the program. The robot system model and the environment map model are established. The motion control model and the odometer model are established respectively for the robot motion control and pose estimation for the omnidirectional mobile robot configuration in this paper. For the main sensor laser sensor modeling correction and coordinate system transformation, the semantic topology layer map and 2D grid layer map are constructed to meet the needs of semantic navigation. Secondly, The problem of robot localization and semantic navigation is studied. The particle distribution of AMCL localization algorithm is guided by semantic constraints in order to accelerate the convergence speed of robot localization and reduce the mismatch phenomenon. The path planning of semantic topology layer adopts the search method based on connected region, which can accelerate the speed of searching and enhance the passability of the narrow environment of robot, and based on the pedestrian prediction model, the path planning of semantic topology layer can improve the speed of searching. The local path planning of dynamic environment robot is carried out by using the quadratic planning method based on A *. Finally, the experimental platform of omnidirectional mobile robot based on Mecanum wheel is built to locate the stability of the robot and the indoor environment of the robot, respectively. The experimental research on robot semantic navigation and dynamic environment navigation is carried out to verify the reliability of the experimental platform and the feasibility of the above algorithms.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP242

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