臺灣博碩士論文加值系統

為了GPS無法於室內有效使用之困擾，過去研究常使用ZigBee無線感測網路作為解決室內定位方法之一。在相關研究中，主要先於定位環境中規劃出最大幾何形狀(常用矩形)後，再於此幾何形狀上佈置適當定位參考節點。在此幾何面積內待測節點利用收集參考節點之接收強度(RSSI)估算對應距離後，利用三邊(或三角)定位法進行定位估算。當面對定位幾何形狀相同但更大面積時，原提出定位方法收集參考節點之接收強度(RSSI)估算對應距離之解析度會明顯下降，在此過大面積進行定位估算時定位誤差可能會加大，無法達到相同定位解析度要求。另外當原定位方法規劃出之幾何形狀與實際應用環境不同時，必須重新進行定位環境規劃與參考節點佈置。此現象增加了過去方法適應任意環境之複雜性。
為了提出一能夠涵蓋任意室內形狀面積的幾何形狀拓樸，過去我們已經找出最佳定位幾何形狀為正六邊形。因此我們以正六邊形作為單一蜂巢式架構之基本單位，稱為細胞(Cell)，再於此正六邊形邊角上佈置六個參考節點與正中心佈置一個參考節點，接著將正六邊形擴展於整個定位面積上，形成定位範圍。當待測節點位於任意兩個相鄰細胞邊界時，由於使用的硬體在近距離的訊號解析度較差，容易造成待測節點收集相鄰細胞之參考節點RSSI值大小相近，導致無法清楚估算相對的遠近距離，容易造成細胞選擇判斷錯誤。為了解決容易誤選定位細胞的問題，本文將提出一新的雙層蜂巢式架構。該架構作法為將每個參考節點設置成兩層架構，首先設置第一層細胞擴展於整個定位面積上，同時以水平與垂直位移1/3正六邊形距離佈置第二層細胞擴展於整個定位面積上。接著提出一新的定位細胞選擇方法，稱為雙層細胞選擇策略。該策略為根據待測節點收集周圍之參考節點RSSI值強弱判斷其所在之細胞編號。接著使用作者所提出的動態混和三邊定位法進行定位估算。從實驗結果顯示經由本文提出之策略皆能正確選擇定位細胞，並維持原有定位方法之解析度。最後，本文將此定位方法實際結合於自走車，並於另一室內進行自走車導引應用。為了避免自走車移動時因硬體機構所造成的定位誤差，容易造成分析定位結果時失真，首先提出一種校正實驗，用以解決驅動系統在移動時的移動誤差。在最小化硬體移動誤差的基礎上，緊接著針對本文定位方法作為室內自走車導航應用的拓樸架構，進行實驗並分析。從實驗結果顯示自走車移動時皆能保持良好的定位效果，證實本文提出的定位方法確實可以成為良好的室內定位選項。

In order to face the weakness of GPS used in indoor environments, the ZigBee systems have widely discussed to be as a possible solution in recent years. In the previous studies, the proposed methods were often considered to shape a geometric topology (e.g., rectangle) to fit the whole area of the experiment environment, and then to arrange suitable number of reference nodes on the area of the geometric topology. The anchor node receives the RSSI values of its around reference nodes to estimate the distance between the anchor node and each reference node, and then applies the Trilateration method to evaluate its location. In practice, the new applied positioning area could be much larger than the former designed one. In this case, the result will be worse than the original design because the accuracy of estimated distance by using RSSI value is decayed due to the increase of distances between the anchor node and each reference node. In addition, when the original designed geometric topology is unsuitable to fit the contour of new applied positioning area, it needs to redesign the system. In other words, it means that the method needs to be considered for adapting different cases and then it increases the complexity to apply for various environments.
In our previous study, we presented a hexagonal topology to arrange the reference nodes to fit all different contours and sizes of applied positioning areas. We first setup a fixed size of regular hexagonal area (called a cell) with reference nodes put on six hexagonal vertices and one on its center. Then, we use our previous proposed dynamic hybrid trilateral positioning method to do the positioning task. As the results, a better positioning accuracy is obtained than it is with rectangular topology. Then, we arrange the cells (regular hexagons) to cover the whole positioning area, called cellular structure. According to the 7 most strength of RSSI values received from all reference nodes, we proposed a rule to judge the correct cell of the anchor node located. When the anchor is located near the border between two adjacent cells (called blurred border) it is possible to make an error judgment to the incorrect cell since the anchor received the almost same level RSSI values from the reference nodes of the two adjacent cells. Therefore, in order to overcome the problem of blurred border, we will propose a new cellular structure called Dual-Cell topology. We first are like the former cellular structure to arrange cells to cover whole positioning area as the first layer. Meanwhile, we arrange cells of the second layer to cover the whole area with each cell is shifted 1/3 hexagonal distance in horizontal and vertical direction to each one of the first layer cells. After the Dual-Cell topology is constructed, the anchor node receives the RSSI values of all around reference nodes. According to the strength arrangement of RSSI values, we will propose a dual-cell decision strategy to select a suitable cell of the anchor node located from the two layers where the anchor can avoid located in the blurred border of the selected cell. When we use the dynamic hybrid trilateral positioning method to do the positioning task, the experimental results show that the proposed strategy can correct all of the wrong cells selected with the former cellular structure.
In addition, we apply our ZigBee dual-cell positioning system to the indoor navigation of a mobile robot to confirm the practicality. In order to avoid the positioning error caused from the hardware of the mobile robot, we will first propose a calibration experiment to correct the errors of the four wheels driving system. After minimizing the positioning error from the hardware, the proposed positioning system is performed by the mobile robot in our Lab and then is analyzed. The analysis results show the high positioning resolution and good performing stability. As a result, the positioning system is not only to be a valuable indoor positioning scheme, but also can be developed in the future for the applications of mobile robots used in any indoor area size.

摘要..........i
Abstract..........ii
誌謝..........v
目錄..........vi
表目錄..........viii
圖目錄..........x
第一章緒論..........1
第二章相關研究..........4
2.1實驗設備與開發環境介紹..........4
2.2通道模型建立之方法..........7
2.3三邊定位法之優化定位幾何..........9
2.4動態混和三邊定位法..........12
第三章雙層蜂巢式架構任意室內面積定位法..........14
3.1雙層蜂巢式架構建置..........15
3.2雙層蜂巢式策略..........19
3.3雙層蜂巢式架構之實驗分析..........21
第四章雙層蜂巢式架構自走車應用..........30
4.1自走車硬體機構校正誤差實驗..........30
4.2雙層蜂巢式架構之自走車實驗..........37
4.3自走車實驗分析..........49
第五章結論..........60
參考文獻..........61
附錄A..........64
附錄B..........65
Extended Abstract..........66

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