题名

PI-BOT: REAL-TIME AUTONOMOUS PAVEMENT DISTRESS SURVEY ROBOT

并列篇名

PI-bot：自主式鋪面破損即時檢測機器人

DOI

10.6652/JoCICHE.201803_30(1).0001

作者

李正豪(Cheng-Hao Lee)；康仕仲(Shih-Chung Kang)；張家瑞(Jia-Ruey Chang)；陳奕竹(Yi-Chu Chen)；蔡孟涵(Meng-Han Tsai)

关键词

pavement inspection system ； robotics ； autonomous inspection ； image processing ； chromatic dual-light inspection ； 鋪面檢測系統 ； 機器人 ； 自主式檢測 ； 影像處理 ； 彩色雙光源檢測

期刊名称

中國土木水利工程學刊

卷期/出版年月

30卷1期（2018 / 03 / 01）

页次

1 - 15

内容语文

英文
中文摘要

Pavement inspection is one of the most important tasks for the maintenance and rehabilitation (M&R) of transportation road surfaces. There are four shortcomings, as follows, in current pavement inspection systems for project-level inspection: time consuming and labor intensive, inefficient and inaccurate, and require post-processing. In order to deal with these drawbacks, this research developed and designed a real-time autonomous pavement inspection robot, called the PI-bot. We also developed the innovative Chromatic Dual-Light Inspection (CDLI) method, integrated with the PI-bot, which can provide distress-enhanced and spillage-removed effects to find distresses. For experiments, we acquired 504 images and tested the performance of the PI-bot and CDLI method. The results show that the CDLI method performs well for normal pavements, alligator cracks, and manholes, and the performance of CDLI in identifying spillage pavements and longitudinal and transverse cracks is also very successful. This research demonstrates that this real-time pavement inspection system is workable and has high potential for pavement inspection tasks. This system is expected to reduce manpower and cost for pavement inspection applications.
英文摘要

鋪面檢測是長期鋪面維護以及修繕工程的重要工作項目，長期鋪面維護及修繕工程通常是耗時且耗人力的。本研究開發一式自主式舖面破損即時檢測機器人：PI-bot，能夠在短距且小範圍的鋪面進行檢測，同時亦研發適用於機器人檢測的彩色雙光源檢測方法(CDLI)與PI-bot進行整合。以實地擷取的504張影像進行實驗測試，並測試CDLI方法的成效。研究結果證明，在一般正常鋪面、鱷魚狀裂縫和人手孔方面有相當好的檢測成果，在污漬鋪面以及縱向橫向裂縫的鋪面上，也可達到滿意的成效，證明PI-bot可有效地執行鋪面檢測工作，減少未來路面檢測之人力與成本。
主题分类 工程學 > 土木與建築工程
工程學 > 水利工程
工程學 > 市政與環境工程
参考文献
  1. Ahmed, M. F. M.,Haas, C. T.(2010).Potential of low cost close range photogrammetry towards unified automatic pavement distress surveying.Proceedings of the 89th Annual Meeting,Washington, DC, USA:
  2. Bennett, D.,Velinsky, S. A.(2009).,University of California at Davis, Department of Mechanical & Aeronautical Engineering.
  3. Borenstein, J.,Koren, Y.(1989).Real-time obstacle avoidance for fast mobile robots.IEEE Transactions on Systems, Man, and Cybernetics,19(5),1179-1187.
  4. Bursanescu, L.,Blais, F.(1997).Automated pavement distress data collection and analysis: A 3-D approach.Proceedings of International Conference on Recent Advances in 3-D Digital Imaging and Modeling,Ottawa, Ont., Canada:
  5. Canny, J.(1987).A computational approach to edge detection.IEEE Transactions on Pattern Analysis and Machine Intelligence,8(6),679-698.
  6. Chang, J. R.,Tseng, Y. H.,Kang, S. C.,Tseng, C. H.,Wu, P. H.(2007).The study in using an autonomous robot for pavement inspection.Proceedings of the 24th International Symposium on Automation and Robotics in Construction,Kochi, India:
  7. Cheng, H. D.,Jiang, X. H.,Glazier, C.(2001).Novel approach to pavement cracking detection based on neutral network.Transportation Research Board,1764,119-127.
  8. Cheng, H. D.,Jiang, X. H.,Glazier, C.,Hu, Y. G.(1999).Novel approach to pavement cracking detection based on fuzzy set theory.Journal of Computing in Civil Engineering,13(4),270-280.
  9. Cortes, C.,Vapnik, V.(1995).Support-vector networks.Machine Learning,20(3),273-297.
  10. Gu, K. Y.,Liu, P.,Chan, J. R.,Kang, S. C.,Hsieh, S. H.(2008).Implementation of an autonomous robot for pavement inspection.Proceedings of the 12th International Conferences on Computing in Civil and Building Engineering,Beijing, China:
  11. Guralinick, S. A.,Suen, E. S.,Smith, C.(1993).Automating inspection of highway pavement surfaces.Journal of Transportation Engineering,119(1),1-12.
  12. Haas, C.,Hendrickson, C.(1991).Integration of diverse technologies for pavement sensing.Transportation Research Record,1311,92-102.
  13. Huang, Y.,Xu, B.(2006).Automatic inspection of pavement cracking distress.Journal of Electronic Imaging,15(1),013017.
  14. Hughes, J. F.,van Dam, A.,McGuire, M.,Sklar, D. F.,Foley, J. D.,Feiner, S. K.,Akeley, K.(2013).Computer Graphics: Principles and Practice.USA:Addison-Wesley Professional.
  15. Jahanshahi, M. R.,Jazizadeh, F.,Masri, S. F.,Becerik-Gerber, B.(2012).Unsupervised approach for autonomous pavement-defect detection and quantification using an inexpensive depth sensor.Journal of Computing in Civil Engineering,27(6),743-754.
  16. Kaseko, M. S.,Ritchie, S. G.(1993).A neural network-based methodology for pavement crack detection and classification.Transportation Research Part C: Emerging Technologies,1(4),275-291.
  17. Lee, B. J.,Lee, H.(2004).Position-invariant neural network for digital pavement crack analysis.Journal of Computer-Aided Civil and Infrastructure Engineering,19(2),105-118.
  18. Li, Q.,Yao, M.,Yao, X.,Xu, B.(2010).A real-time 3D scanning system for pavement distortion inspection.Measurement Science and Technology,21(1),015702.
  19. Madanat, S.(1993).Incorporating inspection decisions in pavement management.Transportation Research Part B: Methodological,27(6),425-438.
  20. Metta, G.,Fitzatrick, P.,Natale, L.(2006).YARP: Yet another robot platform.International Journal on Advanced Robotics Systems,3(1),43-48.
  21. Miller, J. S.,Bellinger, W. Y.(2014).,Virginia:US Department of Transportation, Federal Highway Administration.
  22. Peng, Q.,Wang, K.,Qui, Y.,Pu, Y.,Luo, X.,Shuai, B.(2007).Experimentation of 3D pavement imaging through stereovision.Proceedings of First International Conference on Transportation Engineering,Chengdu, China:
  23. Rababaah, H.,Vrajitoru, D.,Wolfer, J.(2005).Asphalt pavement crack classification: a comparison of GA, MLP, and SOM.Proceedings of the Genetic and Evolutionary Computation Conference,Washington, DC, USA:
  24. Shihab, K.,Chalabi, N.(2009).A hybrid approach to intelligent autonomous mobile robots.Proceeding of the Second International Conference on the Applications of Digital Information and Web Technologies,London, UK:
  25. Su, Y. S.,Kang, S. C.,Chang, J. R.,Hsieh, S.H.(2010).Using dual lights for robotic pavement inspection.Proceedings of SICE Annual Conference 2010,Taipei, Taiwan:
  26. Tsai, Y. C. J.,Li, F.(2012).Critical assessment of detecting asphalt pavement cracks under different lighting and low intensity contrast conditions using emerging 3D laser technology.Journal of Transportation Engineering,138(5),649-656.
  27. Tseng, Y. H.,Kang, S. C.,Chang, J. R.,Lee, C. H.(2011).Strategies for autonomous robots to inspect pavement distresses.Automation in Construction,20(8),1156-1172.
  28. Wang, K. C.,Gong, W.(2005).Real-time automated survey system of pavement cracking in parallel environment.Journal of Infrastructure Systems,11(3),154-164.
  29. Yang, M.,Lo, C. F.(2000).Real-time kinematic GPS positioning for centimeter level ocean surface monitoring.Proceedings of National Science Council,24(1),79-85.
  30. Yu, S. J.,Sukumar, S. R.,Koschan, A. F.,Page, D. L.,Abidi, M. A.(2007).3D reconstruction of road surfaces using an integrated multi-sensory approach.Optics and Lasers in Engineering,45(7),808-881.
  31. Zhou, J.,Huang, P. S.,Chiang, F. P.(2006).Wavelet-based pavement distress detection and evaluation.Optical Engineering,45(2),027007.
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