本文關鍵詞： 港口AGV 自主導航 單目視覺里程計 路徑規(guī)劃 動態(tài)避障　出處：《集美大學》2015年碩士論文　論文類型：學位論文

【摘要】：我國港口集裝箱吞吐總量已經(jīng)連續(xù)十年位居全球第一,然而這卻給傳統(tǒng)的港口運輸模式帶來空前壓力,國外在20世紀90年代開始將AGV系統(tǒng)應用于港口水平運輸,從而大幅度提高了港口集裝箱的運轉效率,但目前應用于港口AGV的導引系統(tǒng)都是基于固定路徑的模式,這種方式簡單可靠,但靈活性較差,智能化程度不高。近年來,隨著圖像處理技術和計算機技術的發(fā)展,基于視覺導航技術受到廣泛關注,本課題基于NI的Starter KIT移動小車搭建了單目視覺系統(tǒng),利用單目視覺技術解決了港口AGV的自主定位、路徑規(guī)劃和避障等問題,對港口AGV完全自主導航的實現(xiàn)進行了探索性研究。主要工作如下:(1)港口AGV單目視覺里程計定位系統(tǒng)設計。利用攝像機獲取的連續(xù)圖像信息推算港口AGV的位姿變化,主要針對SIFT特征點提取和匹配進行了改進,提出了一種實時性和準確性都較好的單目視覺里程計算法,進而能夠實時準確獲取AGV的位姿。(2)港口AGV的全局路徑規(guī)劃。根據(jù)港口環(huán)境結構化程度較高的特點,考慮了AGV運行時能量消耗和安全性,對A*算法的評價函數(shù)進行了改進,設計了一種適合港口環(huán)境的全局路徑規(guī)劃算法。(3)港口AGV的局部路徑規(guī)劃。以單目視覺系統(tǒng)實時獲取的道路平面為樣本,基于道路平面的顏色特征提出了一種自適應圖像分割的障礙物檢測算法,利用單目幾何定位技術確定障礙物的位置,根據(jù)子目標和障礙物的位置選擇通往目的地的最佳航向角。(4)硬件設計和導航系統(tǒng)軟件編程。搭建了港口AGV實驗平臺,利用D-link-DIR617無線路由器搭建局域網(wǎng),實現(xiàn)了AGV、IP攝像機和上位機的無線通信,采用Lab VIEW和MATLAB混合編程設計了港口AGV自主導航和遠程控制軟件。(5)在搭建的模擬港口環(huán)境內(nèi)完成了港口AGV實驗車的遠程控制和自主導航實驗。在遠程控制模式下,根據(jù)IP攝像機獲取的實時道路信息,通過Lab VIEW發(fā)布的共享變量對AGV進行遠程控制。在自主導航模式下,港口AGV實驗車完成了自主定位、路徑規(guī)劃和避障實驗,實驗結果表明基于單目視覺系統(tǒng)的自主導航算法具有較好的魯棒性。
[Abstract]:The total volume of container throughput in China has been ranked first in the world for ten consecutive years. However, this has brought unprecedented pressure to the traditional port transportation mode. In 1990s, foreign countries began to apply AGV system to port level transportation. Therefore, the efficiency of port container operation is greatly improved, but at present, the guidance system used in port AGV is based on the fixed path mode. This method is simple and reliable, but the flexibility is poor, and the degree of intelligence is not high in recent years. With the development of image processing technology and computer technology, visual navigation technology has been paid more and more attention. In this paper, a monocular vision system based on NI Starter KIT mobile vehicle is built, and the independent positioning of port AGV is solved by using monocular vision technology. Path planning and obstacle avoidance, This paper makes an exploratory study on the realization of complete autonomous navigation of port AGV. The main work is as follows: 1) the design of port AGV monocular visual mileometer positioning system. The position and orientation changes of port AGV are calculated by using the continuous image information obtained by the camera. In this paper, the feature points extraction and matching of SIFT are improved, and a monocular visual mileage calculation method with good real-time and accuracy is proposed. Furthermore, the global path planning of the port AGV can be obtained in real time and accurately. According to the characteristics of the higher structural degree of the port environment, the energy consumption and security of the AGV running time are considered, and the evaluation function of the A * algorithm is improved. In this paper, a global path planning algorithm for port environment is designed. The local path planning of port AGV is presented. The road plane obtained in real time by monocular vision system is taken as a sample. Based on the color features of road plane, an adaptive obstacle detection algorithm for image segmentation is proposed. The hardware design and software programming of navigation system are designed according to the optimal heading angle to the destination. The port AGV experimental platform is built, and the local area network is built by using D-link-DIR617 wireless router. Realized the wireless communication between the AGVN IP camera and the host computer. The port AGV autonomous navigation and remote control software. 5) is designed by using Lab VIEW and MATLAB. The remote control and autonomous navigation experiment of the port AGV experimental vehicle is completed in the simulated port environment. According to the real-time road information obtained by IP camera, the remote control of AGV is carried out through the shared variables published by Lab VIEW. In autonomous navigation mode, the port AGV experimental vehicle has completed autonomous positioning, path planning and obstacle avoidance experiments. Experimental results show that the autonomous navigation algorithm based on Monocular vision system is robust.
【學位授予單位】：集美大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：U653.92;TP23

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