為了降低勞力成本以及達到流程標準化，機器人最早被開發應用於製造工業以及農業等產業，以滿足流程標準化及自動化等需求，隨著軟硬體開發成本降低，機器人開始被轉型應用於人類的日常生活中，然而使用環境與互動對象的不同，生活機器人在設計上面臨新的挑戰，例如要處理人類常出現不可預期之反應，因此透過遠端遙控的概念設計機器人系統，使其能解決各種突發狀況，並有效提升生活品質與便利性，但網路連線速率的不確定性會使人類在使用遠端遙控系統時會發生各種操作失誤，雖然已有各種的遠端遙控技術可以修正此類操作失誤，但這些技術都是為專業人士所設計，例如遠端手術中的醫師以及太空遙控機器人的工程師等，然而我們認為在科技如此發達的時代，遠端遙控技術也能應用於一般大眾的日常生活中，故本論文將提出一套改善網路延遲所造成的遠端遙控錯誤方法，使用者不需經過專業訓練就能透過此修正機制降低人為失誤的發生機率，提高各項動作的準確度。

在遠端遙控系統中，使用者通常會透過視訊串流得到遙控端的情況，並經由TCP/IP將控制訊息傳送到遠端進行遙控，因此本論文將建立一套以RTP串流回報遙控端的狀態，並以TCP/IP發送指令的遙控系統架構，在此遙控系統中還包含網路模擬器WANem，利用此套網路模擬器，我們可以輕鬆的調整各項網路參數，利如延遲、封包遺失等等，使得驗證方法時能夠貼近現實的網路情況。而此套遙控架構也以模組化的方式進行開發，善用Java的物件封裝特性，使得開發者能簡單且迅速的套用各種改善遠端遙控錯誤的機制。

本論文提出兩種修正錯誤的機制，此兩種修正機制都是藉由觀察使用者的操控行為進而推導出其預期的範圍與目標，第一種機制可以根據折返的動作推斷使用者想要使物體到達的區域範圍，如此一來就能限制物體的移動範圍，達到降低誤差軌跡的效果，第二種機制則是根據使用者的結束動作時間與網路延遲狀況推算使用者想要使物體到達的確切目標點，並依此目標點進行物體的速度控制，讓使用者能更順暢的將物體移動至他想要的目標位置。實驗則是採用論文中所提到的人類動作模型進行模擬實驗。

In order to reduce labour costs and improve standardization of work process, robots were used in manufacturing industry and agriculture. With advances in technology and reduction cost both in software and hardware development, robots have been used in daily life. Even though the technology of autonomous robots is under sustained development, there are some high-risk or unpredictable tasks that cannot be completed by those robots. With the implementation of remote control technology, we can accomplish the tasks which cannot be done by the robot on its own. However, remote controls would be effected by the network delay which causes inefficient operation. Even though there are several existing applications where robots can be remotely controlled. But, the operators of those applications are trained experts, such as doctors and engineers. We think that along with the improvement of technology, the remote control system should be adapted not only in the specialised field, but also in our daily life. In this thesis, we introduces firstly the basic structure of a remote control system, and analysis the fault caused by network delay. Then, it will be specified how a human action predicting method can fix the mistake caused by human error automatically.

In this thesis, we developed a remote control system. In this system, the operator can move the object to a particular position by sending TCP/IP packets to remote application. And the RTP transmitter will stream the video back to the operators. There is a network simulator included in this system. With the simulator we can adjust various parameters of network such as delay easily. And the validation of the proposed solution could be more realistic.

We proposed two methods to improve human control error. The first one is Target Area Predictor (TAP). TAP estimates the bound of target area. After getting the bound, we can limit the object in the area. The second one is Stop Position Predictor (SPP). SPP predicts the stop position where the operator wants to reach. While moving the object close to the point, SPP slows down the object. Hence the operator can move the object more accurately. Finally, we use the human simulator to evaluate the performance of our proposed solutions.

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