發(fā)布時(shí)間：2019-01-02 09:18

【摘要】：隨著全球科技的不斷進(jìn)步,移動(dòng)機(jī)器人技術(shù)得到了快速的發(fā)展。目前移動(dòng)機(jī)器人已經(jīng)逐漸應(yīng)用于各行各業(yè),并且發(fā)揮著積極重要的作用。但隨著移動(dòng)機(jī)器人應(yīng)用環(huán)境復(fù)雜性的不斷提高,使得以往單機(jī)器人的執(zhí)行能力不能滿足復(fù)雜任務(wù)的要求,所以多機(jī)器人合作技術(shù)成為當(dāng)今機(jī)器人研究的熱點(diǎn)之一。多機(jī)器人之間的合作離不開機(jī)器人之間位置信息的獲取,因此本論文主要研究基于全景視覺的多機(jī)器人協(xié)調(diào)定位系統(tǒng),該系統(tǒng)旨在完成多機(jī)器人之間識別與定位以及提高多機(jī)器人之間的定位精度。本文通過實(shí)際搭建的移動(dòng)機(jī)器人平臺(tái)驗(yàn)證了機(jī)器人目標(biāo)識別與定位、自適應(yīng)令牌環(huán)網(wǎng)絡(luò)通信、數(shù)據(jù)融合定位等相關(guān)方法的可靠性和穩(wěn)定性。具體的研究內(nèi)容如下:首先,根據(jù)移動(dòng)機(jī)器人運(yùn)動(dòng)靈活、價(jià)格便宜、易于控制等要求,本文設(shè)計(jì)并搭建了移動(dòng)機(jī)器人運(yùn)動(dòng)平臺(tái),在該運(yùn)動(dòng)平臺(tái)的基礎(chǔ)上,對機(jī)器人整體方案進(jìn)行具體設(shè)計(jì),其中包括:機(jī)器人整體軟硬件框架設(shè)計(jì)、傳感器選型與配置、底層運(yùn)動(dòng)控制系統(tǒng)設(shè)計(jì)、自適應(yīng)令牌環(huán)網(wǎng)通信設(shè)計(jì)。其次,關(guān)于機(jī)器人全景視覺系統(tǒng),本文給出了視覺處理的具體過程。在目標(biāo)體的識別過程中,本文設(shè)計(jì)了一種易識別、結(jié)構(gòu)簡單、可替換的機(jī)器人目標(biāo)體,同時(shí)給出了一種基于極坐標(biāo)下的全景成像識別方法,該方法簡單有效,可以快速識別多個(gè)目標(biāo)機(jī)器人的特征點(diǎn)。針對識別出的機(jī)器人目標(biāo)體的特征點(diǎn),本文提出了一種改進(jìn)的K-means算法,該算法可以快速有效地得出其它機(jī)器人的坐標(biāo)和角度。通過實(shí)驗(yàn)標(biāo)定,可得出其它機(jī)器人相對自身的實(shí)際距離和角度,同時(shí)還驗(yàn)證了令牌環(huán)網(wǎng)絡(luò)的實(shí)時(shí)性和穩(wěn)定性。再次,對于多機(jī)器人協(xié)調(diào)定位以及定位精度提高方面,本文建立了基于航位推算的機(jī)器人底層運(yùn)動(dòng)模型。結(jié)合機(jī)器人之間的網(wǎng)絡(luò)信息共享以及視覺系統(tǒng)下多目標(biāo)的情況,本文利用電子羅盤坐標(biāo)統(tǒng)一性的特點(diǎn)對多機(jī)器人目標(biāo)進(jìn)行解算匹配,從而建立了機(jī)器人觀測模型,結(jié)合機(jī)器人的運(yùn)動(dòng)模型和觀測模型,本文建立了多機(jī)器人之間定位狀態(tài)方程,最后利用擴(kuò)展卡爾曼(EKF)算法對各個(gè)模型數(shù)據(jù)進(jìn)行融合,通過實(shí)驗(yàn)驗(yàn)證了該方法提高了機(jī)器人之間的定位精度。最后,本文對多機(jī)器人協(xié)作定位系統(tǒng)進(jìn)行了總結(jié)與展望,希望通過本文提出的方案與算法,為后期研究多機(jī)器人合作奠定基礎(chǔ)。
[Abstract]:With the continuous progress of global science and technology, mobile robot technology has been rapid development. At present, mobile robots have been gradually used in various industries, and play an active and important role. However, with the increasing complexity of mobile robot application environment, the execution ability of single robot can not meet the requirements of complex tasks in the past, so multi-robot cooperation technology has become one of the hotspots of robot research. The cooperation between multi-robots can not be separated from the acquisition of position information between robots. Therefore, this paper mainly studies the coordinated localization system of multi-robots based on panoramic vision. The purpose of this system is to realize the identification and localization of multi-robots and to improve the positioning accuracy of multi-robots. In this paper, the reliability and stability of robot target recognition and localization, adaptive token ring network communication and data fusion localization are verified by the mobile robot platform. The specific research contents are as follows: firstly, according to the requirements of mobile robot, such as flexible motion, cheap price and easy control, this paper designs and builds the mobile robot motion platform, based on the motion platform, The overall scheme of the robot is designed, including: the overall hardware and software framework design, sensor selection and configuration, the bottom motion control system design, adaptive token ring network communication design. Secondly, regarding the robot panoramic vision system, this paper gives the concrete process of vision processing. In the process of object recognition, this paper designs a robot object which is easy to recognize, simple in structure and replaceable. At the same time, a panoramic image recognition method based on polar coordinates is presented, which is simple and effective. The feature points of multiple target robots can be quickly identified. In this paper, an improved K-means algorithm is proposed for identifying the characteristic points of the target body of the robot. This algorithm can quickly and effectively obtain the coordinates and angles of other robots. Through the experimental calibration, the actual distance and angle of other robots relative to their own can be obtained, and the real-time and stability of the token ring network can also be verified. Thirdly, for the coordination of multi-robot positioning and the improvement of positioning accuracy, this paper establishes the robot bottom motion model based on dead-reckoning. Combined with the sharing of network information among robots and the situation of multi-targets under visual system, this paper makes use of the unity of electronic compass coordinates to solve and match the multi-robot targets, and then establishes the robot observation model. Combined with the motion model and observation model of the robot, the state equation of multi-robot localization is established in this paper. Finally, the extended Kalman (EKF) algorithm is used to fuse the data of each model. The experimental results show that this method can improve the positioning accuracy of robots. Finally, this paper summarizes and prospects the multi-robot cooperative positioning system, hoping to lay a foundation for the later study of multi-robot cooperation through the proposed scheme and algorithm.
【學(xué)位授予單位】：安徽工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP242

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