Chinese
Adv Search
Home | Accepted | Article In Press | Current Issue | Archive | Special Issues | Collections | Featured Articles | Statistics

2020, 2(2): 87-103 Published Date:2020-4-20

DOI: 10.1016/j.vrih.2020.04.003

Intelligent virtualization of crane lifting using laser scanning technology

Full Text: PDF (22) HTML (555)

Export: EndNote | Reference Manager | ProCite | BibTex | RefWorks

Abstract:

Background
This paper presents an intelligent path planner for lifting tasks by tower cranes in highly complex environments, such as old industrial plants that were built many decades ago and sites used as tentative storage spaces. Generally, these environments do not have workable digital models and 3D representations are impractical.
Methods
The current investigation introduces the use of cutting-edge laser scanning technology to convert real environments into virtualized versions of the construction sites or plants in the form of point clouds. The challenge is in dealing with the large point cloud datasets from the multiple scans needed to produce a complete virtualized model. The tower crane is also virtualized for the purpose of path planning. A parallelized genetic algorithm is employed to achieve intelligent path planning for the lifting task performed by tower cranes in complicated environments taking advantage of graphics processing unit technology, which has high computing performance yet low cost.
Results
Optimal lifting paths are generated in several seconds.
Keywords: Laser scanning ; Point cloud ; Intelligent modeling ; Virtualization of complex environments ; Virtual tower crane ; Automatic lifting path planning ; Rasterization

Cite this article:

Lihui HUANG, Souravik DUTTA, Yiyu CAI. Intelligent virtualization of crane lifting using laser scanning technology. Virtual Reality & Intelligent Hardware, 2020, 2(2): 87-103 DOI:10.1016/j.vrih.2020.04.003

1. Lin K L, Haas C T. An interactive planning environment for critical operations. Journal of Construction Engineering and Management, 1996, 122(3): 212‒222 DOI:10.1061/(asce)0733-9364(1996)122:3(212)

2. Varghese K, Dharwadkar P, Wolfhope J, O'Connor J T. A heavy lift planning system for crane lifts. Computer-Aided Civil and Infrastructure Engineering, 1997, 12(1): 31‒42 DOI:10.1111/0885-9507.00044

3. Al-Hussein M, Athar Niaz M, Yu H T, Kim H. Integrating 3D visualization and simulation for tower crane operations on construction sites. Automation in Construction, 2006, 15(5): 554‒562 DOI:10.1016/j.autcon.2005.07.007

4. Kang S C, Chi H L, Miranda E. Three-dimensional simulation and visualization of crane assisted construction erection processes. Journal of Computing in Civil Engineering, 2009, 23(6): 363‒371 DOI:10.1061/(asce)0887-3801(2009)23:6(363)

5. Chadalavada S, Madras G, Varghese K. Development of a computer aided critical lift planning system using parametric modeling software. In: Proceedings of the 2010 (1st) International Conference on Engineering, Project, and Production Management, Association of Engineering, Project, and Production Management, 2010, 1–12 DOI:10.32738/ceppm.201010.0001

6. Wang X, Lv Y L, Wu D. Development of tower crane simulation system with flexible wire rope. In: Proceedings of the 2015 International Symposium on Computers and Informatics. Beijing, China, Paris, France, Atlantis Press, 2015, 2416–2423 DOI:10.2991/isci-15.2015.314

7. Sivakumar P, Varghese K, Babu N R. Path planning of construction manipulators using genetic algorithms. In: Proceedings of the 16th IAARC/IFAC/IEEE International Symposium on Automation and Robotics in Construction. Madrid, Spain. International Association for Automation and Robotics in Construction (IAARC), 1999, 555–560 DOI:10.22260/isarc1999/0086

8. Ali M S A D, Babu N R, Varghese K. Collision free path planning of cooperative crane manipulators using genetic algorithm. Journal of Computing in Civil Engineering, 2005, 19(2): 182–193 DOI:10.1061/(asce)0887-3801(2005)19:2(182)

9. Reddy H R, Varghese K. Automated path planning for mobile crane lifts. Computer-Aided Civil and Infrastructure Engineering, 2002, 17(6): 439–448 DOI:10.1111/0885-9507.00005

10. Olearczyk J, Bouferguène A, Al-Hussein M, Hermann U R. Automating motion trajectory of crane-lifted loads. Automation in Construction, 2014, 45: 178–186 DOI:10.1016/j.autcon.2014.06.001

11. Lin Y S, Wu D, Wang X, Wang X K, Gao S D. Lift path planning for a nonholonomic crawler crane. Automation in Construction, 2014, 44: 12–24 DOI:10.1016/j.autcon.2014.03.007

12. AUTODESK. Plant Design Suite. http://www.autodesk.com/suites/plant-design-suite/overview. 2016-1-4

13. AVEVA. Solutions for the plant industries. http://www.aveva.com/en/Products_and_Services/AVEVA_for_Plant.aspx. 2016-1-4

14. INTERGRAPH. SmartPlant® Enterprise. http://www.intergraph.com/products/ppm/smartplant/. 2016-1-4

15. Izadi S, Kim D, Hilliges O, Molyneaux D, Newcombe R, Kohli P, Shotton J, Hodges S, Freeman D, Davison A, Fitzgibbon A. KinectFusion: Real-time 3D reconstruction and interaction using a moving depth camera. ACM, New York, USA, 2011, 559–568

16. Henry P, Krainin M, Herbst E, Ren X F, Fox D. RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments. The International Journal of Robotics Research, 2012, 31(5): 647–663 DOI:10.1177/0278364911434148

17. Hornung A, Wurm K M, Bennewitz M, Stachniss C, Burgard W. OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Autonomous Robots, 2013, 34(3): 189–206 DOI:10.1007/s10514-012-9321-0

18. Olearczyk J, Al-Hussein M, Bouferguène A. Evolution of the crane selection and on-site utilization process for modular construction multilifts. Automation in Construction, 2014, 43: 59–72 DOI:10.1016/j.autcon.2014.03.015

19. Marzouk M, Abubakr A. Decision support for tower crane selection with building information models and genetic algorithms. Automation in Construction, 2016, 61: 1–15 DOI:10.1016/j.autcon.2015.09.008

20. Huang C, Wong C K, Tam C M. Optimization of tower crane and material supply locations in a high-rise building site by mixed-integer linear programming. Automation in Construction, 2011, 20(5): 571–580 DOI:10.1016/j.autcon.2010.11.023

21. Lien L C, Cheng M Y. Particle bee algorithm for tower crane layout with material quantity supply and demand optimization. Automation in Construction, 2014, 45: 25–32 DOI:10.1016/j.autcon.2014.05.002

22. Wang J, Zhang X D, Shou W C, Wang X Y, Xu B, Kim M J, Wu P. A BIM-based approach for automated tower crane layout planning. Automation in Construction, 2015, 59: 168–178 DOI:10.1016/j.autcon.2015.05.006

23. Carricato M, Merlet J P. Stability analysis of underconstrained cable-driven parallel robots. IEEE Transactions on Robotics, 2013, 29(1): 288–296 DOI:10.1109/tro.2012.2217795

24. Gouttefarde M, Collard J F, Riehl N, Baradat C. Geometry selection of a redundantly actuated cable-suspended parallel robot. IEEE Transactions on Robotics, 2015, 31(2): 501–510 DOI:10.1109/tro.2015.2400253

25. Park J, Chung W K, Moon W. Wire-suspended dynamical system: stability analysis by tension-closure. IEEE Transactions on Robotics, 2005, 21(3): 298–308 DOI:10.1109/tro.2004.840888

26. Oh S R, Agrawal S K. Cable suspended planar robots with redundant cables: controllers with positive tensions. IEEE Transactions on Robotics, 2005, 21(3): 457–465 DOI:10.1109/tro.2004.838029

27. Kang S, Miranda E. Planning and visualization for automated robotic crane erection processes in construction. Automation in Construction, 2006, 15(4): 398–414 DOI:10.1016/j.autcon.2005.06.008

28. Chang Y C, Hung W H, Kang S C. A fast path planning method for single and dual crane erections. Automation in Construction, 2012, 22: 468–480 DOI:10.1016/j.autcon.2011.11.006

29. Cai P P, Cai Y Y, Chandrasekaran I, Zheng J M. A GPU-enabled parallel genetic algorithm for path planning of robotic operators//GPU Computing and Applications. Singapore: Springer Singapore, 2014, 1–13 DOI:10.1007/978-981-287-134-3_1

30. Cai P P, Cai Y Y, Chandrasekaran I, Zheng J M. Parallel genetic algorithm based automatic path planning for crane lifting in complex environments. Automation in Construction, 2016, 62: 133–147 DOI:10.1016/j.autcon.2015.09.007

31. Huang L H, Zhang Y Z, Zheng J M, Cai P P, Dutta S, Yue Y F, Thalmann N, Cai Y Y. Point cloud based path planning for tower crane lifting. In: Proceedings of Computer Graphics International. Bintan, Island, Indonesia, ACM Press, 2018, 211–215 DOI:10.1145/3208159.3208186

32. Cai Y Y, Zheng J M, Zhang Y Z, Wu X Q, Chen Y, Tan B Q, Yang B Y, Liu T R, Thalmann N. Madam snake white: a case study on virtual reality continuum applications for Singaporean culture and heritage at haw par villa. Presence: Teleoperators and Virtual Environments, 2018, 26(4): 378–388 DOI:10.1162/pres_a_00303

33. Golovinskiy A, Funk T. Min-cut based segmentation of point clouds. In: 2009 IEEE 12th International Conference on Computer Vision Workshops. Kyoto, Japan, IEEE, 2009 DOI:10.1109/iccvw.2009.5457721

34. Rost RJ, Licea-Kane B. Chapter 1. Review of OpenGL Basics. In: OpenGL Shading Language, 3rd edn. Boston, MA, Addison-Wesley, 2009, 1–34

35. NVIDIA. CUDA C Programming Guide. http://docs.nvidia.com/cuda/cuda-c-programming-guide/#axzz3wRH77NnU. 2015-10-3

36. Bouaziz S, Tagliasacchi A, Pauly M. Sparse iterative closest point. In: SGP'13 Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing. 2013, 113–123

email E-mail this page

Articles by authors

VRIH