淡江大學機構典藏:Item 987654321/35298
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/35298


    Title: 機器人移動平臺之全局避障路徑規劃及遠端監控設計
    Other Titles: Global path planning and remote control design for robotic mobility platform
    Authors: 翁崇泰;Weng, Chung-tai
    Contributors: 淡江大學機械與機電工程學系碩士班
    楊智旭;Yang, Jr-syu
    Keywords: 機器人移動平台;路徑規劃;A* 演算法;遠端;伺服端;robotic mobility platform;Segway RMP 50;Path Planning;A* algorithm;client;server
    Date: 2008
    Issue Date: 2010-01-11 06:19:54 (UTC+8)
    Abstract: 本論文研究的目的是以Segway RMP 50作為機器人移動平台，架設成遠端監控機器人，並模擬機器人在已知環境中，以A* 演算法來做路徑規劃，然後以Segway RMP 50來驗證A* 演算法在搭配格點模型建立已知地圖後，可快速找到最佳路徑。
    機器人以Segway RMP 50為平台主體，另外設計承載平台來搭裝控制端的筆記型電腦，及視訊攝影機，未來可加裝各種探測儀器，來探測機器人所在位置的資訊，遠端監控系統是以視訊攝影機所擷取到的影像連接到控制端的筆記型電腦並且建立一伺服端，使用者可利用網路連結到此一伺服端，監控機器人之攝影機所擷取到的即時影像，供使用者得知機器人所在位置的環境資訊。
    為了讓機器人有避障及有路徑規劃的能力，我們使用格點模型建立已知地圖資訊，使用A* 演算法規劃路徑，並模擬Segway RMP 50以簡單的動作規劃然後來遠端遙控行走，根據Segway RMP 50行走的內部里程資訊，來計算路徑的距離，然後比較A* 演算法模擬的路徑及機器人實地行走的誤差。
    The objective of this research is to develop a robotic mobility platform, which using Segway RMP 50 to demonstrate the optimum path planning under A* algorithm and a developed map.
    Segway RMP 50 is the principal platform in this research. The self-designed mechanical loading structured is installed on the RMP 50 to set up the notebook computer/webcam. The robot system is capable to install more sensors to detect the environmental information beside this robot. A client control system is developed to be a server by the webcam and laptop computer. The other users are able to watch the pc screen to find out the related environmental images by the internet from the developed server.
    The A* algorithm and a developed grid map are applied to let this robot be able to avoid obstacle and make an optimum path planning. The simulation results show that the Segway RMP 50 system is capable to make a simple movement planning and to calculate the length of the moving path. Finally, the robot system is demonstrated its ability of obstacle–avoidance and the optimum path planning by the A* algorithm.
    Appears in Collections:[Graduate Institute & Department of Mechanical and Electro-Mechanical Engineering] Thesis

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