隨著定位技術的快速發展,人們逐漸依賴室內定位及導航技術,對於行動裝置的估測位置精準度是不可或缺的.解決發射器與接收器之間的量測誤差是必要的,因為當訊號受到多重路徑干擾(Multipath Interference)的影響,所接收的訊號抵達時間將會比真正訊號抵達時間還要久,因此定位精準度容易被訊號抵達時間所影響並降低準確率.為了解決提到的問題,我們設計出一個簡單且便宜的室內光波定位系統結合演算計算的方式實現高精準度的可見光室內定位.
在計算機科學領域，進化計算可以被視為一種全局優化算法。 以迭代方式模擬“適者生存”的自然選擇機制，將未知問題視為環境，並通過自然進化尋求最佳解決方案（即機器人的位置）。在本研究中,我們使用發光二極體作為發射器,利用每個發射器與機器人之間的訊號飛行時間找出定位資訊,再透過訊號抵達時間差(Time Difference of Arrival, TDOA)得到機器人可能的位置,然後藉由演化計算(Evolutionary Computation)結合不同的目標函數得到更精確機器人的估計位置.根據模擬分析以及實作結果，顯示本論文所提出的方法可以提供更精準行動台位置估測也是用於室內定位系統。

With the rapid development of positioning technology, people gradually rely on indoor positioning and navigation technology, which is indispensable for the accuracy of the estimated position of mobile devices. It is necessary to solve the measurement error between the transmitter and the receiver, because the signal is affected by Multipath Interference, and the arrival time of the received signal will be longer than the real signal arrival time, so the positioning accuracy is easily affected by the signal arrival time and reduces the accuracy rate. In order to solve the mentioned Problem, we designed a simple and cheap indoor light wave positioning system combined with algorithmic calculation to achieve high-precision indoor positioning.
In the field of computer science, evolutionary computing can be regarded as a global optimization algorithm. Iteratively simulates the natural selection mechanism of "survival of the fittest", treats unknown problems as the environment, and seeks the best solution (that is, the position of the robot) through natural evolution. Therefore, in this study, we use the light-emitting diode as the transmitter, use the signal flight time between each transmitter and the robot to find the positioning information, and then obtain the possibility of the robot through the Time Difference of Arrival (TDOA). The position of the robot is then combined with different objective functions by evolutionary calculation to obtain a more accurate estimated position of the robot. According to the simulation analysis and implementation results, it is shown that the method proposed in this paper can provide more accurate mobile station position estimation and is also used for indoor positioning system.

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