臺灣博碩士論文加值系統

摘要
最近幾年，遠距健康照護非常盛行，如今社會老年人口攀升，而出生率衰退。導致人口結構產生重大的變化，使得人們對於長期照護的需求日以遽增。在長期照護的前提之下，對於醫療照護人口的需求增加，然而面對需求增加且人力不足應付之時，遠距健康照護的新穎照護方式逐漸被推行於生活之中。
遠距健康照護是透過網路或無線訊號監控受照顧者的生理安全，一旦發生異常情況，監控者能立即進行相關醫療緊急通報、處置或派出訪查專員了解情況，間接節省大量醫療照護成本。但在系統中可能會因某些原因造成誤判，或者是某些緊急情況需要醫療照護，而訪查專員無法立即抵達現場的狀況。因此藉由車型機器人達到即時監控。當車型機器人嘗試抵達意外地點時，室內定位與路徑規劃是必要且影響重大的因素。本研究著重於路徑規劃，以改善車型機器人的移動效率。
現階段的路徑規劃演算法，大多數是以距離作為制定的最短路徑的參照，但是最短路徑並不代表最佳化路徑規劃，其中可能受到周圍環境因素影響，例如轉角、地表材質和地面坡度等，因而使得移動時間成本增加。故本研究假設在已知環境條件之下，著重於避障與最佳化路徑研究。在空間搜索方面，由於環境中障礙物是已知狀態，因此採用圖形搜索演算法(Visibility graph)取得障礙物之頂點，並將頂點加以擴充，以獲得有效避免碰撞的行走節點。而路徑規劃方面，傳統普遍被應用的方式是Dijkstra's演算法或者A-star演算法實現路徑規劃，但上述被普遍應用的演算法之中，卻沒有將轉角的資訊納入考量。在現實生活中，向前或者轉彎的路徑規劃都是需要花費單位成本的，本論文所提供的方式，將路徑距離與轉折角度的資訊連結，使路線產生新的權重，再以Dijkstra's演算法進行演算，找尋最佳化路徑。

Abstract
In recent years, the telehealthcare is very popular. Because the tele-healthcare can keep a watchful eye on information of patients or elderly people, and handle in anytime, in anywhere and by any device, If becomes an on going nursing behavior. Based on its concept, we builded a indoor positioning system by RFID Cartesian grids, which can guide the robocar move to the designated location , then to realize the circumstances with the patient. In this field, many factors will determine whether it can be access or not, such as location-awareness, path finding and path conditions.
In this study, we first introduce passive RFID tags to act as landmarks for solving location-awareness. These landmarks can not only read by robocar to determine present localization but reduce computing time for path finding searching process. For the part of path –planning, we proposed an improved graph-based algorithm for archiving obstacles avoidance and less veers into consideration, to generate an efficient path for navigation.
We tested the efficiency of different path finding algorithms with the designated map, included Dijkstra’s algorithm, the collision–free algorithm (CFA) on basis of Dijkstra and our proposed method. In comparison of Dijkstra’s algorithm and CFA approach, Dijkstra’s algorithm could find the shortest path. but easily occur collision; and although CFA approach increase 3% distances, it could ensure keeping up a collision-free condition. Another aspect, in comparison of our proposed approach and CFA approach, our method increase cruising distance then CFA, due to it isn’t a shortest path . However, the aim we adopted veering angles is to emend weighting manner to condition of mobile robocar cruising. And our result proved the ideal shortest path is not minimum time to access destinations in practical environment.

目錄
摘要 ii
Abstract iv
致謝 vi
目錄 vii
表目錄 ix
圖目錄 x
1 第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 10
1.3 章節規劃 10
1.4 本章小結 11
2 第二章 文獻回顧 12
2.1 環境定位 12
2.1.1 紅外線(Infrared Ray) 13
2.1.2 超音波(Ultrasonic) 14
2.1.3 無線區域網路IEEE802.11(Wireless LAN) 15
2.1.4 無線射頻辨識 (Radio Frequency Identification, RFID) 16
2.2 無線射頻辨識RFID介紹 18
2.2.1 起源 18
2.2.2 RFID原理 19
2.2.3 電子標籤(Transponder) 20
2.2.4 讀取器(Reader) 25
2.3 無線訊號定位技術 26
2.3.1 訊號抵達角度法(Arrival of Angle, AOA) 27
2.3.2 訊號抵達時間法(Time of Arrival, TOA) 28
2.3.3 訊號抵達時間差法(Time difference of Arrival, TDOA) 30
2.3.4 訊號強度法(Received Signal Strength Indication, RSSI) 31
2.4 路徑規劃 32
2.4.1 Regular grids 34
2.4.2 Waypoint graphs 34
2.4.3 Navigation meshes 35
2.4.4 Visibility graph 36
2.4.5 Dijkstra’s algorithm 36
2.4.6 A-star algorithm 38
2.5 本章小結 40
3 第三章 實驗材料與方法 41
3.1 研究工具 41
3.2 研究方法與步驟 41
3.2.1 RFID定位演算法 42
3.2.2 規劃路徑之重要節點表示法 44
3.2.3 最佳路徑演算法 47
3.3 本章小結 51
4 第四章 實驗結果與討論 52
4.1 實驗環境 52
4.2 實驗一實驗設計 52
4.3 實驗一實驗結果 54
4.4 實驗二實驗設計 55
4.5 實驗二實驗結果 56
4.6 本章小結 60
5 第五章 結論與未來展望 62
參考文獻 63




















表目錄
表 2 1 RFID應用種類形式 20
表 2 2 電子標籤特性分類 24
表 2 3 規劃流程 37
表 4 1 路線花費成本比較 58





























圖目錄
圖 1 1 各國人口平均壽命 1
圖 1 2 人口推計預測 2
圖 1 3 國內生產總值 2
圖 1 4 男女人口結構分布圖 4
圖 1 5 2007年美國遠距監測市場 5
圖 1 6 Intel Mobile Clinical Assistant 6
圖 1 7 Microsoft HealthVault[12] 7
圖 1 8 Fujitsu遠距照護支援系統 8
圖 2 1 Infrared location system 12
圖 2 2 ULTRASONIC TRACKING AND LOCATING SYSTEM 13
圖 2 3 Microsoft Radio-frequency based system 15
圖 2 4 RFID系統運作原理 19
圖 2 5 電子標籤內部結構 20
圖 2 6 頻率應用列表 21
圖 2 7 電磁感應 22
圖 2 8 微波傳播 22
圖 2 9 讀取器硬體配置 25
圖 2 10 讀取器種類樣式 25
圖 2 11 Arrival of Angle 27
圖 2 12 Time of Arrival 29
圖 2 13 Time difference of Arrival 30
圖 2 14 Received Signal Strength Indication, RSSI 31
圖 2 15 圖形理論(Graph theory) 32
圖 2 16 Regular grids 33
圖 2 17 Waypoint graphs 34
圖 2 18 Navigation meshes 34
圖 2 19 Visibility graph 35
圖 2 20 Dijkstra’s 搜尋演算法範例 36
圖 2 21 4-drections和8- directions行走方式 38
圖 3 1 佈建方式 41
圖 3 2 模擬佈建環境 42
圖 3 3 標記障礙物頂點 44
圖 3 4 障礙物頂點向外擴張 45
圖 3 5 空間搜索流程 45
圖 3 6 可形成的路徑 46
圖 3 7 可行走的路徑 47
圖 3 8 角度計算範例 48
圖 3 9 路徑規劃結果 48
圖 3 10 路徑規劃流程 49
圖 4 1 Map size 8*8範例 52
圖 4 2 Map size 16*16範例 53
圖 4 3 路徑規劃效率統計 54
圖 4 4 路徑規劃範例 55
圖 4 5 傳統Dijkstra’s演算法執行路徑規劃結果 56
圖 4 6 擷取障礙物外擴頂點的Dijkstra’s演算法執行路徑規劃結果 57
圖 4 7 本研究所提供改善方案執行路徑規劃結果 57

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