研究生: |
陳立哲 Li-che Chen |
---|---|
論文名稱: |
在有障礙物的空間內進行多機械人的派工服務 Multi-Robot Dispatching in a Geographically Constrained Environment |
指導教授: |
鍾聖倫
Sheng-Luen Chung 項天瑞 Tien-Ruey Hsiang |
口試委員: |
林其禹
Chi-Yu Lin 郭重顯 Chung-Hsien Kuo 鄭慕德 Mu-Der Jeng |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電機工程系 Department of Electrical Engineering |
論文出版年: | 2008 |
畢業學年度: | 96 |
語文別: | 英文 |
論文頁數: | 86 |
中文關鍵詞: | 多機器人 、派班系統 、最短路徑法則 、k-means演算法 、Steiner tree演算法 |
外文關鍵詞: | Multi-robot, dispatching system, the shortest path approach, k-means algorithm, Steiner tree algorithm |
相關次數: | 點閱:216 下載:2 |
分享至: |
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在集中式多機器人系統中,系統會依照機器人的能力與數量,將一項完整的任務分成若干個子任務,再分配給多隻機器人系統去執行,透過這樣的分工方式,提高整體工作效率。除此之外,當有機器人發生故障時,其餘的機器人仍能接替完成該任務,使系統具有較佳的強健性。然而,隨著負責的工作量增加,機器人的數目卻未隨之增加,系統必須要提供一個有效的資源分配方式,使每隻機器人皆能適得其所並發揮所長。
本論文提供了一個基於k-means與Steiner tree演算法之多機器人任務分配系統。該方法可適用在一般的大樓環境中,藉由縮短回應任務請求之時間,使機器人在最短的時間內,執行完所指定的任務,以提昇系統工作效率。在有障礙物的環境中,該系統透過最短路徑法則,計算出機器人與欲執行任務之距離,再由k-means演算法將任務請求點分群並指派給機器人負責管理,接著根據Steiner tree演算法在所指派群集中找出最佳的待命位置,使系統達到縮短回應任務請求時間之訴求。除此之外,在機器人執行任務時,本論文也提供了一個多機器人的合作模式,透過機器人的相互支援,更加縮短了任務執行的時間。最後,透過系統的模擬以及實際軟硬體的整合,使本論文所提出的方法得以驗證與實現。
In the centralized multi-robot system, a full task is accomplished by dividing it into several subtasks and distributing these subtasks to the individual robots. Thus, the efficiency can be increased by executing the subtasks simultaneously. In addition, if any robot is out of service, the others can take over its task instantly, thus increasing the robustness of the system. However, as the number of tasks increase, the system is constrained by the fact that there are more requesting points than available robots. In this situation, the key challenge of the multi-robot system is how to coordinate these robots to achieve a satisfactory performance of the overall task.
To address this, we present a task-allocation approach, based on the k-means with Steiner tree algorithm, to dispatch a platoon of mobile robots in a constrained environment. It is capable to increase the efficiency of the multi-robot tasks execution by reducing the task response time. The proposed method clusters the requesting points based on the k-means algorithm. Then, the robots are pre-positioned in the standby point of their assigned clusters according to the k-means with Steiner tree algorithm. In this method, the distance in the obstacle environment is calculated by the shortest path approach. In addition, a switching strategy of the robots is also presented in this thesis. By switching the clusters, the robots can share the workload. Thus, the total task execution time can be reduced. The efficiency of the proposed methods is demonstrated through simulation study and practical implementation.
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