標題: 利用自動車作基於視覺之室內安全巡邏
Vision-Based Security Patrolling in Indoor Environments Using Autonomous Vehicles
作者: 陳明哲
Ming-Che Chen
蔡文祥
Wen-Hsiang Tsai
資訊科學與工程研究所
關鍵字: 安全巡邏;自動車;導航;Security patrolling;robot;autonomous vehicle;navigation strategy
公開日期: 2004
摘要: 本研究主要是提出一套基於電腦視覺技術,可讓自動車航行在室內環境中且具有安全監控的能力。我們利用一台小型自動車為實驗平台,並且利用無線操控的方式讓自動車航行在室內的環境中。我們設計了一套人簡單且有效的學習方式,讓使用者可以操控自動車行走且自由的選擇要被監控的物品或是房門,自動車將會自動的建立導航的地圖。在學習完路線、物品和門的資料之後,我們運用了一套完整的導航策略來完成安全巡邏的任務。這個策略包括了監控物品的安全偵測和房門情況的識別,利用自動車判斷物品是否遭竊或者是門被開起,我們能夠立刻發出警報給使用者,已達成安全巡邏的任務。最後我們以成功的學習與導航實驗結果證明本系統的完整性與可行性。
A vision-based approach to security patrolling in indoor environments using autonomous vehicles is proposed. A small vehicle with wireless control and image grabbing capabilities is used as a test bed. Three stages of security patrolling are proposed. First, a simple learning strategy is designed for flexible and effective learning of reachable spots and monitored objects in indoor environments. Accordingly, a planned path is obtained, and monitored objects and doors are specified by analyzing user commands. Next, following the learned path, the vehicle can accomplish specified navigation sessions. Two different kinds of methods, mechanic error correction modeling and vehicle position modification by positions of monitored objects, are proposed for navigation accuracy maintenance. Finally, an object matching algorithm is used for checking the existence of monitoring objects and the opening status of doors. All the experimental results show flexibility and feasibility of the proposed approach for the application of indoor security patrolling.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT009223624
http://hdl.handle.net/11536/76674
Appears in Collections:Thesis


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