Hostname: page-component-54dcc4c588-scsgl Total loading time: 0 Render date: 2025-10-01T17:38:17.480Z Has data issue: false hasContentIssue false
  • English
  • Français

Fast and efficient visible trajectories planning for the Dubins UAV model in 3D built-up environments

Published online by Cambridge University Press:  02 August 2013

Oren Gal  and
Yerach Doytsher
Oren Gal*
Affiliation:
Mapping and Geo-Information Engineering, Technion, Israel Institute of Technology, Haifa, Israel
Yerach Doytsher
Affiliation:
Mapping and Geo-Information Engineering, Technion, Israel Institute of Technology, Haifa, Israel
*
*Corresponding author. E-mail: orengal@tx.technion.ac.il
Get access Rights & Permissions [Opens in a new window]

Summary

In this paper, we study the visible trajectories planning for unmanned aerial vehicles (UAVs) modeled with a Dubins airplane in 3D urban environments. Our method is based on a fast and exact spatial visibility analysis of the 3D visibility problem from a viewpoint in 3D built-up environments. We consider the 3D urban environment buildings modeled as cubes (3D boxes) and present an analytic solution to the visibility problem. Based on an analytic solution, the algorithm computes the exact visible and hidden parts from a viewpoint in the urban environment. We present a local trajectory planner generating the most visible trajectory in a known 3D urban environment model, taking into account the dynamic and kinematic UAV constraints. The planner computes, at each time step, the next UAV's attainable velocities and explores the most visible node, while avoiding buildings as static obstacles in the environments, using the velocity obstacle method. The visibility type of the trajectory can be configured beforehand as visible roofs and surfaces in the environments. We demonstrate our visibility and trajectory planning method in simulations in several 3D urban environments, showing visible trajectory planning capabilities.

Keywords

Trajectory planning3D Urban environmentsSpatial analysisVisibility

Information

Type
Articles
Information
Robotica , Volume 32 , Issue 1 , January 2014 , pp. 143 - 163
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

1.Elber, G., Sayegh, R., Barequet, G. and Martin, R., “Two-Dimensional Visibility Charts for Continuous Curves,” Proceedings of Shape Modeling, MIT, Boston, USA (2005) pp. 206–215.Google Scholar
2.Gal, O. and Doytsher, Y., “Fast and Accurate Visibility Computation in a 3D Urban Environment,” Proceedings of the Fourth International Conference on Advanced Geographic Information Systems, Applications, and Services, Valencia, Spain (2012) pp. 105–110.Google Scholar
3.Gal, O. and Doytsher, Y., “Fast Visibility Analysis in 3D Procedural Modeling Environments,” Proceedings of the 3rd International Conference on Computing for Geospatial Research and Applications, Washington DC, USA (2012).Google Scholar
4.Fiorini, P. and Shiller, Z., “Motion planning in dynamic environments using velocity obstacles,” Int. J. Robot. Res. 17, 760–772 (1998).CrossRefGoogle Scholar
5.Office of the Secretary of Defense, Unmanned Aerial Vehicles Roadmap, Tech. Rep., December (2002).Google Scholar
6.Latombe, J. C., Robot Motion Planning (Kluwer Academic Press, 1990).Google Scholar
7.Erdman, M., and Lozano-Perez, T., “On multiple moving objects,” Algorithmica 2, 477–521 (1987).CrossRefGoogle Scholar
8.Fraichard, T., “Trajectory planning in a dynamic workspace: a ‘state-time space’ approach,” Adv. Robot. 13, 75–94 (1999).CrossRefGoogle Scholar
9.LaValle, S. M. and Kuffner, J., “Randomized Kinodynamic Planning,” Proceedings of the IEEE International Conference on Robotics and Automation, Detroit, MI, USA (1999) pp. 473–479.Google Scholar
10.Mao, Z. H., Feron, E. and Bilimoria, K., “Stability and performance of intersecting aircraft flows under decentralized conflict avoidance rules,” IEEE Trans. Intell. Transport. Syst. 2, 101–109 (2001).Google Scholar
11.Bellingham, J., Richards, A. and How, J., “Receding Horizon Control of Autonomous Aerial Vehicles,” Proceedings of the IEEE American Control Conference, Anchorage, AK, USA (2002) pp. 3741–3746.Google Scholar
12.Sinopoli, B., Micheli, M., Donata, G. and Koo, T., “Vision Based Navigation for an Unmanned Aerial Vehicle,” Proceedings of the IEEE International Conference on Robotics and Automation (2001).Google Scholar
13.Sasiadek, J. and Duleba, I., “3D local trajectory planner for UAV,” J. Intell. Rob. Syst. 29, 191–210 (2000).CrossRefGoogle Scholar
14.Bortoff, S. A., “Path Planning for UAVs,” Proceedings of the American Control Conference, Chicago, IL, USA (2000) pp. 364–368.Google Scholar
15.Plantinga, H. and Dyer, R., “Visibility, occlusion, and aspect graph,” Int. J. Comput. Vis. 5, 137–160 (1990).CrossRefGoogle Scholar
16.Doytsher, Y. and Shmutter, B., “Digital Elevation Model of Dead Ground,” Proceedings of the Symposium on Mapping and Geographic Information Systems (Commission IV of the International Society for Photogrammetry and Remote Sensing), Athens, Georgia, USA (1994).Google Scholar
17.Durand, F., 3D Visibility: Analytical Study and Applications PhD Thesis (Universite Joseph Fourier, Grenoble, France, 1999).Google Scholar
18.Franklin, W. R., “Siting Observers on Terrain,” Proceedings of 10th International Symposium on Spatial Data Handling, Springer-Verlag (2002) pp. 109–120.CrossRefGoogle Scholar
19.Wang, J., Robinson, G. J. and White, K., “A fast solution to local viewshed computation using grid-based digital elevation models,” Photogramm. Eng. Remote Sens. 62, 1157–1164 (1996).Google Scholar
20.Wang, J., Robinson, G. J. and White, K., “Generating viewsheds without using sightlines,” Photogram. Eng. Remote Sens. 66, 87–90 (2000).Google Scholar
21.Ratti, C., “The lineage of line: space syntax parameters from the analysis of urban DEMs',” Environ. Plan. Plan. Des. 32, 547–566 (2005).CrossRefGoogle Scholar
22.De Floriani, L. and Magillo, P., “Visibility algorithms on triangulated terrain models,” Int. J. Geograph. Inf. Syst. 8, 13–41 (1994).Google Scholar
23.Nadler, B., Fibich, G., Lev-Yehudi, S. and Cohen-Or, D., “A qualitative and quantitative visibility analysis in urban scenes,” Comput. Graph. 5, 655–666 (1999).CrossRefGoogle Scholar
24.LaValle, S. M., Planning Algorithms (Cambridge University Press, Cambridge, UK, 2006).CrossRefGoogle Scholar
25.Hwangbo, M., Kuffner, J. and Kanade, T., “Efficient Two-phase 3D Motion Planning for Small Fixed-wing UAVs,” Proceeding of the 2007 IEEE International Conference on Robotics and Automation, ICRA 2007, Roma, Italy (Apr. 10–14, 2007).Google Scholar
26.http://www.asctec.de/uav-applications/research/products/asctec-hummingbird/.Google Scholar
27.Bhatia, A., Graziano, M., Karaman, S., Naldi, R. and Frazzoli, E., “Dubins Trajectory Tracking Using Commercial Off-the-Shelf Autopilots,” Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, Honolulu, Hawaii (Aug. 18–21, 2008).Google Scholar
28.Chitsaz, H. and LaValle, S. M., “Time-Optimal Paths for a Dubins Airplane,” Proceedings of the IEEE Conference on Decision and Control, USA (2007) pp. 2379–2384.Google Scholar
29.Zlatanova, S., Rahman, A. and Wenzhong, S., “Topology for 3D spatial objects,” Proceedings of the International Symposium Exhibition on Geoinformation (2002) pp. 22–24.Google Scholar
30.Franklin, W. R. and Ray, C., “Higher isn't necessarily better: visibility algorithms and experiments,” In: Advances in GIS Research: Sixth International Symposium on Spatial Data Handling (Waugh, T. C. and Healey, R. G., eds.) (Taylor & Francis, Edinburgh, 1994) pp. 751–770.Google Scholar