The main objective of the system presented in this paper is to provide surveyors and engineers with a new photogrammetry device that can be easily integrated with surveying total stations and a global navigation satellite system (GNSS) infrastructure at a construction site, taking advantage of their accuracy and overcoming limitations of aerial vehicles with respect to weight, autonomy and skilled operator requirements in aerial photogrammetry. The system moves between two mounting points, in a blondin ropeway configuration, at the construction site, taking pictures and recording the data of the position and the orientation along the cable path. A cascaded extended Kalman filter is used to integrate measurements from the on-board inertial measurement unit (IMU), a GPS and a GNSS. Experimental results taken in a construction site show the system performance, including the validation of the position estimation, with a robotic surveying total station, or the creation of a digital surface model (DSM), using the emergent structure from motion (SfM) techniques and open software. The georeferencing of the DSM is performed based on estimated camera position or using ground control points (GCPs).
References
[1]
Lloret, P. Inertial+total Station+GPS for High Productivity Surveying. Proceedings of the Position Location and Navigation Symposium, Las Vegas, NV, USA, 20–23 March 1990; pp. 338–346.
[2]
Gikas, V. Three-dimensional laser scanning for geometry documentation and construction management of highway tunnels during excavation. Sensors 2012, 12, 11249–11270.
[3]
Park, H.S.; Son, S.; Choi, S.W.; Kim, Y. Wireless laser range finder system for vertical displacement monitoring of mega-trusses during construction. Sensors 2013, 13, 5796–5813.
[4]
Siu, M.F.; Lu, M.; AbouRizk, S. Combining photogrammetry and robotic total stations to obtain dimensional measurements of temporary facilities in construction field. Vis. Eng. 2013, doi:10.1186/2213-7459-l-4.
[5]
El-Omari, S.; Moselhi, O. Integrating 3D laser scanning and photogrammetry for progress measurement of construction work. Autom. Constr. 2008, 18, 1–9.
[6]
Fregonese, L.; Barbieri, G.; Biolzi, L.; Bocciarelli, M.; Frigeri, A.; Taffurelli, L. Surveying and monitoring for vulnerability assessment of an ancient building. Sensors 2013, 13, 9747–9773.
[7]
Eisenbeiss, H. Photogrammetry. Doctoral Thesis, Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, Switzerland, 2009.
[8]
Skaloud, J.; Vallet, J.; Keller, K.; Veyssière, G.; K？lbl, O. An eye for landscapes: Rapid aerial mapping with handheld sensors. GPS World 2006, 17, 26–32.
[9]
Peterman, V.; Mesariè, M. Land Survey from Unmmaned Aerial Vehicle. Proceedings of International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B1, 2012 XXIIISPRS Congress, Melbourne, Australia, 25 August–1 September 2012; pp. 447–452.
[10]
Dorninger, P.; Pfeifer, N. A comprehensive automated 3D approach for building extraction, reconstruction, and regularization from airborne laser scanning point clouds. Sensors 2008, 8, 7323–7343.
[11]
Manyoky, M.; Theiler, P.; Steudler, D.; Eisenbeiss, H. Unmanned Aerial Vehicle in Cadastral Applications. Proceedings of International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXVIII-1/C22 UAV-g 2011, Conference on Unmanned Aerial Vehicle in Geomatics, Zurich, Switzerland, 14？16 September 2011; pp. 1–6.
[12]
Wallace, L.; Lucieer, A.; Watson, C.; Turner, D. Development of a UAV-LiDAR system with application to forest inventory. Remote Sens. 2012, 4, 1519–1543.
[13]
Chiabrando, F.; Nex, F.; Piatti, D.; Rinaudo, F. UAV and RPV systems for photogrammetric surveys in archaelogical areas: Two tests in the Piedmont region (Italy). J. Archaeol. Sci. 2011, 38, 697–710.
[14]
Turner, D.; Lucieer, A.; Watson, C. An automated technique for generating georectified mosaics from ultra-high resolution unmanned aerial vehicle (UAV) imagery, based on structure from motion (SfM) point clouds. Remote Sens. 2012, 4, 1392–1410.
[15]
Aber, J.S.; Aber, S.W.; Pavri, F. Unmanned Small-format Aerial Photography from Kites for Acquiring Large-scale, High-resolution, Multiview-angle Imagery. Proceedings of the Pecora. 15/Land Satellite Information IV/ISPRS Commission (I/FIEOS 2002), Denver, CO, USA, 10–14 November 2002.
[16]
Watts, A.C.; Ambrosia, V.G.; Hinkley, E.A. Unmanned aircraft systems in remote sensing and scientific research: Classification and considerations of use. Remote Sens. 2012, 4, 1671–1692.
[17]
Nex, F.; Remondino, F. UAV for 3D mapping applications: A review. Appl. Geomat. 2013, 1–15.
[18]
Chao, H.; Coopmans, C.; Di, L.; Chen, Y.Q. A Comparative Evaluation of Low-cost IMUs for Unmanned Autonomous Systems. Proceedings of IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems, Salt Lake City, UT, USA, 5？7 September 2010; pp. 211–216.
[19]
Kingston, D.B.; Beard, R.W. Real-time Attitude and Position Estimation for Small UAVs Using Low-cost Sensors. Proceedings of AIAA 3rd Unmanned Unlimited Technical Conference, Workshop and Exhibit, Chicago, IL, USA, 21？23 September 2004; pp. 2004–6488.
[20]
Noureldin, A.; Karamat, T.B.; Georgy, J. Fundamentals of Inertial Navigation, Satellite-based Positioning and Their Integration; Springer: Berlin/Heidelberg, Germany, 2013.
[21]
Hofmann-Wellenhof, B.; Lichtenegger, H.; Wasle, E. GNSS Global Navigation Satellite Systems; Springer: Berlin/Heidelberg, Germany, 2008.
[22]
Seo, J.; Lee, H.K.; Lee, J.G.; Park, C.G. Lever arm compensation for GPS/INS/Odometer integrated system. Int. J. Control Autom. Syst. 2006, 4:2, 247–254.
[23]
Gavrilets, V. Autonomous Aerobatic Maneuvering of Miniature Helicopters. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 2003.
[24]
Wang, Y.; Yang, X.; Stojic, M.; Skelton, B. Toward Higher Automation and Flexibility in Commercial Digital Photogrammetric System. Proceedings of International Archives of Photogrammetry and Remote Sensing, Volume IC WG II/IV, Istambul, Turkey, 12–23 July 2004; pp. 838–840.
[25]
Wu, C. VisualSFM: A Visual Structure from Motion System. 2011. Available online: http://ccwu.me/vsfm/ (accessed on 11 October 2013).
[26]
Snavely, N.; Seitz, S.M.; Szeliski, R. Modeling the world from internet photo collections. Int. J. Comput. Vis. 2008, 80, 189–210.
[27]
Furukawa, Y.; Ponce, J. Accurate, dense, and robust multi-view stereopsis. IEEE Trans. Pattern Anal. 2009, 32, 1362–1376.
[28]
Snavely, N. Bundler: Structure from Motion (SfM) for Unordered Image Collections. Available online: phototour.cs.washingtonedu/bundler/ (accessed on 11 October 2013).
[29]
Wu, C. Towards Linear-time Incremental Structure from Motion. Proceedings of 2013 International Conference on 3DTV-Conference, Seattle, WA, USA, 29 June–1 July 2013; pp. 127–134.
[30]
Wu, C. SiftGPU: A GPU Implementation of Scale Invaraint Feature Yransform (SIFT). 2007. Available online: cs.unc.edu/～ccwu/siftgpu/ (accessed on 11 October 2013).
[31]
Pierrot-Deseilligny, M.; Cléry, I. APERO, an Open Source Bundle Adjustment Software for Automatic Calibration and Orientation of a Set of Images. Proceedings of International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-5/W16, Trento, Italy, 2–4 March 2011.
[32]
Pierrot-Deseilligny, M.; Paparoditis, N. A Multiresolution and Optimization-based Image Matching Approach: An Application to Surface Reconstruction from SPOT5-HRS Stereo Imagery. Proceedings of International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI-1/W41, Ankara, Turkey, 14？16 Februrary 2006.
[33]
Rothermel, M.; Wenzel, K.; Fritsch, D.; Haala, N. SURE: Photogrammetric Surface Reconstruction from Imagery. Proceedings of LC3D Workshop, Berlin, Germany, 4–5 December 2012.
[34]
Remondino, E.; Del Pizzo, S.; Kersten, T.; Troisi, S. Low-cost and Open-source Solutions for Automated Image Orientation—A Critical Overview. Proceddings of Euromed, LNCS 7616, Lemesos, Cyprus, 29 October–3 November 2012; pp. 40–54.
[35]
Lingua, A.; Marenchino, D.; Nex, F. Performance analysis of the sift operator for automatic feature extraction and matching in photogrammetric applications. Sensors 2009, 9, 3745–3766.
[36]
Wu, C.; Agarwal, S.; Curless, B.; Seitz, S.M. Multicore Bundle Adjustment. Proceedings of 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA, 21–23 June 2011; pp. 3057–3064.
Kazhdan, M.; Bolitho, M.; Hoppe, H. Poisson Surface Reconstruction. Proceedings of the Fourth Eurographics Symposium on Geometry Processing, Sardinia, Italy, 26–28 June 2006.
[39]
Horn, B.K. Closed-form solution of absolute orientation using unit quaternions. J. Opt. Soc. Am. A 1987, 4, 629–642.
