淡江大學機構典藏:Item 987654321/35789
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/35789


    Title: 結合單體搜尋法之改良式粒子濾波器及其在非線性函數追蹤及機器人定位之研究
    Other Titles: Enhanced particle filter incorporating a nelder-mead simplex search scheme and its applications in nonlinear function tracking and localization of mobile robots
    Authors: 黎乃仁;Li, Nai-jen
    Contributors: 淡江大學電機工程學系碩士班
    許陳鑑;Hsu, Chen-chien
    Keywords: 粒子濾波器;競賽選擇法;單體搜尋法;函數追蹤;均方誤差;室內定位;Particle Filter;tournament selection;simplex search method;function tracking;RMSE;indoor localization
    Date: 2009
    Issue Date: 2010-01-11 07:09:20 (UTC+8)
    Abstract: 本論文提出兩種改良型粒子濾波器(Enhanced Particle Filter, EPF) 演算法,分別混合競賽選擇法(Tournament Selection)以及單體搜尋法(Nelder-Mend Simplex Search, NM)之演算法,針對不同問題調整所需之競賽規模(tournament size),以加快區域搜尋的速度,可以改善傳統粒子濾波器之準確性以及收斂速度,提升粒子濾波器之性能。為驗證所提出之演算法的效果,本文亦針對非線性一維函數追蹤的問題,估測每一時刻函數可能的狀態,並隨著時間重複計算每時刻的狀態之均方誤差(Root Mean Square Error, RMSE),以此評估演算法之好壞,另外,對於非線性四維目標物函數追蹤問題,本論文所提出之方法亦有相當傑出的效果。本論文最後再以改良型粒子濾波器應用在輪型機器人之室內定位(indoor localization)之模擬,以一虛擬地圖模擬輪型機器人於室內環境中行走。模擬結果顯示,提出的改良型粒子濾波器在室內環境下,能夠有效並確地定位出機器人所在之位置與方向。
    In this thesis, an enhanced particle filter incorporating tournament selection and Nelder-Mead (NM) simplex search method is proposed to improve the performance of function tracking for nonlinear functions. Simulation results show that more accurate results on state estimation for the nonlinear functions in terms of RMSE can be obtained by using the proposed particle filter in comparison with existing approaches. Finally, the enhanced particle filter is applied to indoor localization of mobile robot. The simulation result shows the method which estimates position and direction of mobile robot effectively.
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Thesis

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