淡江大學機構典藏:Item 987654321/114773
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 62830/95882 (66%)
造訪人次 : 4128420      線上人數 : 362
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧：
  • 您可在西文檢索詞彙前後加上"雙引號"，以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋，建議至進階搜尋限定作者欄位，可獲得較完整資料
    •  進階搜尋


    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/114773


    題名: 基於ROS之人形機器人的影像定位與導航
    其他題名: ROS-based visual localization and navigation for humanoid robot
    作者: 簡瑜萱;Chien, Yu-Hsuan
    貢獻者: 淡江大學電機工程學系碩士班
    翁慶昌
    關鍵詞: A* algorithm;A*演算法;Image Localization;Monte Carlo localization;Particle Filter;Particle Swarm Optimization (PSO);Robot Operating System (ROS);粒子群最佳化法;粒子濾波器;蒙地卡羅定位;影像定位;機器人作業系統
    日期: 2017
    上傳時間: 2018-08-03 15:03:37 (UTC+8)
    摘要: 本論文針對視覺自主之小型人形機器人提出一個基於機器人作業系統(Robot Operating System, ROS)之定位與導航的實現方法。在Linux環境下，以ROS建構人形機器人的軟體開發架構，在視覺系統中，本論文將影像中感興趣的顏色，以人工標記的方式標記作為特徵，並利用逆透視映射法(Inverse Perspective Mapping, IPM)計算出障礙物與機器人間的距離，以此作為定位的依據。在定位系統中，本論文建立一個有障礙物資訊的虛擬地圖，以機器人移動量做為位移資訊，並且以視覺影像做為系統觀測的資訊，再以蒙地卡羅(Monte Carlo)自我定位法搭配上結合粒子群最佳化法(Particle Swarm Optimization, PSO)之粒子濾波器(particle filter)演算法來推算小型人形機器人的位置。在導航系統中，本論文以改良式A*演算法來規劃一個具有較少轉折點的全域規劃路徑。由實驗結果可得知，本論文所設計之小型人形機器人的定位與導航系統，可使機器人在已知環境中具有自我定位及導航的能力，且安全的避開障礙物並順利抵達目的地。
    In this thesis, a localization and navigation system is proposed to be implemented on Robot Operating System (ROS) for a vision-based autonomous small-sized humanoid robot. In the Linux environment, ROS is used to establish the software development framework for the humanoid robot system. In the vision system, some interested color blocks in the image are marked as features, and Inverse Perspective Mapping (IPM) is used to calculate the distance between the obstacle and robot. In the localization system, a virtual map with some obstacle information is established. The amount of movement of the robot is regarded as displacement information, and the visual image is regarded as observation information. Then a method based on the Monte Carlo self-localization method and the particle filter combined with Particle Swarm Optimization (PSO) algorithm is used to estimate the localization for the small-sized humanoid robot. In the path planning system, a modified A* algorithm is proposed to plan a global path planning which has less turning points. From the experimental results, we can see that the proposed localization and navigation system really lets the small-sized humanoid robot has the ability of self-localization and navigation in a known environment. Moreover, the robot can safely avoid obstacles and successfully reach the destination.
    顯示於類別:[電機工程學系暨研究所] 學位論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML130檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋