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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 康仕仲 | |
dc.contributor.author | Kai-Yuan Gu | en |
dc.contributor.author | 古凱元 | zh_TW |
dc.date.accessioned | 2021-06-13T15:41:00Z | - |
dc.date.available | 2008-07-14 | |
dc.date.copyright | 2008-07-14 | |
dc.date.issued | 2008 | |
dc.date.submitted | 2008-07-07 | |
dc.identifier.citation | Abaza, K. A., Ashur, S. A., & Al-Khatib, I. A. (2004). Integrated Pavement Management System with a Markovian Prediction Model. Journal of Transportation Engineering, ASCE, Vol. 130, No. 1 , pp. 24-33.
[2] ARRB. (1965). ARRB Group Ltd. Retrieved 6 10, 2008, from http://www.arrb.com.au/ [3] ASTM D5340. (2004). Standard Practice of Roads and Parking Lots Pavement Condition Index Surveys. [4] ASTM D6433. (2003). Standard Practice of Roads and Parking Lots Pavement Condition Index Surveys. [5] Darter, I. M., & Shahin, Y. M. (1980). Pavement Rehabilitation: Identifying the Need. Journal of Transportation Engineering, ASCE, Vol. 106, No. 1 , pp. 1-10. [6] Diosi, A., & Kleeman, L. (2007, October 10). Fast Laser Scan Matching using Polar Coordinates. The International Journal of Robotics Research Vol. 26 , pp. 1125-1153. [7] Dynatest. (1976). Retrieved 6 15, 2008, from The Dynatest® Group: http://www.dynatest.com/ [8] Federal Highway Administration. (1989, 7). Automated Pavement Condition Data Collection Equipment. Retrieved 6 20, 2008, from DOT On-Line Publications: DOT On-Line Publications [9] International Federation of Robotics(IFR). (2008). Key data. Retrieved 05 19, 2008, from World Robotics Market 2006: http://www.ifr.org/modules.php?name=News&file=article&sid=9 [10] Joseph Budras, P. E. (2001, 8). A Synopsis on the Current Equipment Used for Measuring Pavement Smoothness - Smoothness - Pavements - FHWA. Retrieved 6 26, 2008, from Federal Highway Administration Home Page: http://www.fhwa.dot.gov/PAVEMENT/smoothness/rough.cfm [11] Liptak, B. (1995). Instrument Engineers 'Handbook: Process Control'. Radnor, Pennsylvania: Chilton Book Company, 20-29. [12] Lu, F., & Milios, E. (1994). Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans. Journal of Intelligent and Robotic Systems 18 , pp. 935-938. [13] Microsoft. (2006). Microsoft Robotics Studio. Retrieved 5 21, 2008, from http://msdn.microsoft.com/en-us/robotics/default.aspx [14] NaitoJunpei, O. N. (2006). Development of a Wearable Robot for Assisting Carpentry Workers. International Symposium on Automation and Robotics in Construction (ISARC) , pp. 523-526. [15] Parallax. (2004). BASIC Stamp Syntax and Reference Manual Version 2.1. Retrieved 5 11, 2007, from http://www.parallax.com/dl/docs/prod/stamps/basicstampman.pdf [16] Perera, R. W., & Kohn, S. D. (2005). QUANTIFICATION OF SMOOTHNESS INDEX DIFFERENCES RELATED TO LTPP EQUIPMENT TYPE. 6300 Georgetown Pike, McLean, VA 22101: Federal Highway Administration. [17] Russell, S., & Norvig, P. (2003). Artificial Intelligence: A Modern Approach( Second Edition ). Prentice Hall. [18] Shahin, M. Y. (2005). Pavement Management for Airports, Roads, and Parking Lots, Second Edition. Springer. [19] Van, D. V. (2003). Loop Tuning Fundamentals. Control Engineering. Red Business Information. [20] Yukio, H. (2006). Construction Automation and Robotics in the 21st Century. The International Symposium on Automation and Robotics in Construction (ISARC) , pp. 565-568. [21] 中華鋪面工程學會. (2005). 臺灣地區鋪面管理系統暨檢測設備開發及整合運用之分析專案計畫期中報告. [22] 交通部公路總局. (2007年4月3日). 公路資訊. 2007年5月 擷取自 交通部公路總局: http://www.thb.gov.tw/ [23] 周家蓓, 李怡萱, 蕭翔駿, 陳怡先, 呂佳玲, & 周進發. (2003). 慣性式平坦儀之開發與台北、台中及高雄三市市區道路平坦度檢測結果分析. 第十二屆鋪面工程學術研討會, 頁 659-666. [24] 國立清華大學科技管理學院科技政策研究報告. (2005). 台灣智慧型機器人產業發展機會與策略. 台北市: 經濟部工業局94年度專案計畫執行成果報告. [25] 張家瑞. (2007). 自主式機器人於道路檢測可行性研究. 交通部運輸研究所. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37734 | - |
dc.description.abstract | 本論文發展以自主式機器人進行鋪面檢測之運動模式,其運動模式分為兩大類,其一由人工檢測方式所設計之「全面檢測模式」,另由工程中抽樣檢測概念所設計之「抽樣檢測模式」,再將運動模式由構想層面設計成控制演算法,並以CSharp程式開發出軟體模擬測試環境,用以確保演算法符合運動模式之設計,最後將演算法於硬體實現,建構自主式機器人以印證鋪面檢測運動模式。
在鋪面檢測運動模式之軟體演算法部分,共分為運動模式設計與軟體模擬部分,我們由現行檢測的模式發展為全面檢測模式,其中包含(1)縱向檢測,(2)橫向檢測,及工程抽樣檢測的概念發展出抽樣檢測模式,包含(1)隨機移動檢測,(2)方格檢測等,在透過自行開發之軟體模擬結果中發現,全面檢測模式與抽樣檢測模式有應用上之互補性。以檢測完整道路之時間為考量,全面檢測模式可應用於需要檢測道路完整的資訊,如進行新建道路驗收等,而不同於全面檢測模式以循序漸進的方式進行檢測,抽樣檢測模式採用隨機的行走方式,故若相同時間裡,受檢測路面與未受測路面的平均涵蓋度為考量,抽樣檢測模式可取得均佈的道路資訊。 建置自主式機器人的部分,為避免機器人針對單一問題來設計,導致機器人若要重新處理不同問題,必需花費許多時間與人力成本來改變硬體架構與演算核心。本文之機器人改變傳統的作法,建構出具彈性的軟硬體架構。硬體部分將採用Basic Stamp II單晶片作為訊號處理,運動方式使用全向輪,並利用機器人全向輪的特性,增加兩個特殊運動模式(1)迴避障礙物、(2)定點密集檢測以應用在檢測鋪面破壞點與躲避障礙物時之應用。此機器人在機構採用三層式架構,分別為(1)邏輯運算層、(2)訊號感知層與(3)運動控制層,分別獨立,增加硬體擴充與可修改性。軟體架構則使用Microsoft Robotics Developer Studio(MSRDS),它採用的分散式服務系統設計也基於賦予本研究之機器人更多的彈性,使得當需求改變時,可輕易的變動軟硬體來切合更多的研究主題。 在本論文之運動檢測應用層面提出取得道路真實剖面值的方式,以解決並擴展運動模式於現行檢測中之使用限制與應用範圍,最後在自主式機器人建置的部分,驗證驗算法符合設計,於鋪面檢測運動模式與建構自主式機器人的相關經驗,提供未來相關性研究之參考。 | zh_TW |
dc.description.abstract | We propose novel pavement inspection motion modes for autonomous robots which are generalized into complete inspection modes and sampling inspection modes. Based on these two complementary modes, we are able to provide a robust and efficient pavement inspection algorithm.
In details, complete inspection composes of (i) longitudinal mode and (ii) transversal mode. They are derived from tradition manual pavement inspection methods. Meanwhile, we have sampling inspection compose of (iii) random mode and (iv) grid mode which are derived from sampling inspection methods in the engineering. Then, we carry out data analysis from software simulation. The results show that complete inspection modes are faster than sampling inspection modes when the overall pavement is to be inspected. However, for complete inspection modes where there is a time constraint, sampling inspection modes will be able to cover more road information. The hardware platform is divided into three layers: a motion and sensing module, a control module, and a logic module. Developers can add, remove, or replace modules of all layers with compatible ones at will. The Basic Stamp II (BS-II) signal and control chip is used for the control module. For software, the packaged software Microsoft Robotics Developer Studio (MSRDS) is used to allow for re-use. MSRDS provides Concurrency and Coordination Runtime (CCR) and Decentralized System Services (DSS) for autonomous tasks. The overall hardware components are defined as services in DSS. During runtime, users execute synchronization in CCR. Therefore, the software and hardware of the robot is easy to modify or reuse for different applications. In comparison to previous works, the hardware and software platforms of this robot provide greater flexibility. The robot platform, originally purpose-built for pavement inspections, has now been generalized such that minimal modification would be required for use in different scenarios or applications - reusability of the design has become the central focus. Finally, practical experiments were performed to validate the efficacy of the motion modes. The satisfactory results indicated that integrating pavement inspection research and the autonomous robot has great potential. And we are hopeful the innovative method may be a basis for future researchers in the same field. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T15:41:00Z (GMT). No. of bitstreams: 1 ntu-97-R95521606-1.pdf: 3763578 bytes, checksum: 61ec37328ed387f978b096ec14d092e9 (MD5) Previous issue date: 2008 | en |
dc.description.tableofcontents | 口試委員會審定書.............I
致謝.............II 中文摘要.............V ABSTRACT.............VII 目錄.............IX 表目錄.............XII 圖目錄.............XIII 第一章、緒論.............1 1.1 研究背景.............1 1.2 研究動機.............1 1.3 研究目的與範圍.............4 1.4 研究方法.............5 1.5 論文架構.............8 第二章、鋪面檢測儀器與機器人發展.............11 2.1 鋪面檢測相關儀器發展.............11 2.2 機器人發展與應用面.............19 第三章、機器人鋪面檢測模式.............25 3.1 機器人模型.............25 3.2 全面檢測模式.............26 3.2.1 縱向檢測模式............. 26 3.2.2 橫向檢測模式 .............27 3.3 抽樣檢測模式.............28 3.3.1 隨機移動檢測模式.............29 3.3.2 方格檢測模式 .............29 第四章、軟體模擬驗證.............31 4.1 模擬環境之軟體建置.............31 4.2 演算法測試用之場景與案例.............32 4.2.1 場景說明.............32 4.2.2 案例說明.............33 4.3 模擬結果.............34 4.4 各運動模式應用面.............38 第五章、機器人建置與檢測運動之驗證.............43 5.1 硬體架構.............43 5.2 晶片控制架構.............46 5.3 軟體架構.............48 5.4 運動控制與基礎定位.............53 5.4.1 全向輪運動公式.............54 5.4.2 全向輪特性應用於鋪面檢測.............55 5.4.3 基礎定位法使用Polar Scan Matching.............58 5.5 機器人檢測運動之驗證.............60 5.5.1 縱向檢測法於實體機器人之驗證.............60 5.5.2 橫向檢測法於實體機器人之驗證.............60 5.5.3 隨機移動檢測法於實體機器人之驗證.............64 5.5.4 方格檢測法於實體機器人之驗證.............64 5.5.5 特殊運動模式於實體機器人之驗證.............67 第六章、結論與未來展望.............71 6.1 結論.............71 6.2 未來展望.............72 參考文獻.............75 附錄.............79 附錄A、硬體規格表.............79 | |
dc.language.iso | zh-TW | |
dc.title | 機器人鋪面檢測之運動模式 | zh_TW |
dc.title | Motion Planning Method for Robotics Pavement Inspection | en |
dc.type | Thesis | |
dc.date.schoolyear | 96-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 謝尚賢,周家蓓,李蔡彥,張家瑞 | |
dc.subject.keyword | 自主式機器人,營建自動化,道路檢測, | zh_TW |
dc.subject.keyword | Autonomous robot,Automation in construction,Pavement inspection, | en |
dc.relation.page | 82 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2008-07-07 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
顯示於系所單位: | 土木工程學系 |
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