[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/2525314.2525363acmconferencesArticle/Chapter ViewAbstractPublication PagesgisConference Proceedingsconference-collections
research-article

Computing highly occluded paths on a terrain

Published: 05 November 2013 Publication History

Abstract

Understanding the locations of highly occluded paths on a terrain is an important GIS problem. In this paper we present a model and a fast algorithm for computing highly occluded paths on a terrain. It does not assume the observer locations to be known and yields a path likely to be occluded under a rational observer strategy. We present experimental results that examine several different observer strategies. The repeated visibility map computations necessary for our model is expedited using a fast algorithm for calculating approximate visibility maps that models the decrease in observational fidelity as distance increases. The algorithm computes a multiresolution approximate visibility map and makes use of a graphics processing unit (GPU) to speed up computation. We present experimental results on terrrain data sets with up to 144 million points.

References

[1]
P. K. Agarwal, L. Arge, and K. Yi, I/O-efficient batched union-find and its applications to terrain analysis, ACM Trans. Algorithms 7 (2011), Article 11.
[2]
L. Aleksandrov, H. Djidjev, A. Maheshwari, and J.-R. Sack, An approximation algorithm for computing shortest paths in weighted 3-d domains, Discr. Comput. Geom., 50 (2013), 124--184.
[3]
L. Aleksandrov, A. Maheshwari, and J.-R. Sack, Approximation algorithms for geometric shortest path problems, Proc. 32nd ACM Sypos. Theory. Comput., 2000, pp. 286--295.
[4]
C. Cai and S. Ferrari, Information-driven sensor path planning by approximate cell decomposition, IEEE Transactions on Systems, Man, and Cybernetics, Part B, 39 (2009), 672--689.
[5]
J. Chen and Y. Han, Shortest paths on a polyhedron, Int. J. Comput. Geometry Appl., 6 (1996), 127--144.
[6]
M. de Berg, O. Cheong, M. van Kreveld, and M. Overmars, Computational Geometry: Algorithms and Applications, Springer, 2010.
[7]
H. Edelsbrunner and J. Harer, Computational Topology: An Introduction, American Mathematical Society, 2010.
[8]
W. R. Franklin, M. Inanc, Z. Xie, D. M. Tracy, B. Cutler, and M. V. A. Andrade, Smugglers and border guards: the geostar project at rpi, Proc. ACM-GIS, 2007, pp. 30:1--8.
[9]
M. Hielsberg, R. Tsai, P. Guo, and C. Chen, Visibility-based urban exploration and learning using point clouds, Proc. IEEE/RSJ Intl. Conf. Intell. Robots Sys., 2013.
[10]
K. Klein and S. Suri, Capture bounds for visibility-based pursuit evasion, Proc. 29th Sympos. Comput. Geom., 2013, pp. 329--338.
[11]
Y. Landa and R. Tsai, Visibility of point clouds and exploratory path planning in unknown environments, Commun. Math. Sci., 6 (2008), 881--913.
[12]
S. LaValle, Planning Algorithms, Cambridge University Press, 2006.
[13]
J. Lee and D. Stucky, On applying viewshed analysis for determining least-cost paths on digital elevation models, Intl. J. Geog. Info. Sci., 12 (1998), 891--905.
[14]
M. Lu, J. Zhang, P. Lv, and Z. Fan, Max/min path visual coverage problems in raster terrain, Computer-Aided Design and Computer Graphics, 2007, pp. 497--500.
[15]
D. Luebke, B. Watson, J. D. Cohen, M. Reddy, and A. Varshney, Level of Detail for 3D Graphics, Elsevier Science Inc., 2002.
[16]
L. Lulu and A. Elnagar, A comparative study between visibility-based roadmap path planning algorithms, Proc. IEEE/RSJ Intl. Conf. Intell. Robots Sys., 2005, pp. 3263--3268.
[17]
M. S. Marzouqi and R. A. Jarvis, New visibility-based path-planning approach for covert robotic navigation, Robotica, 24 (2006), 759--773.
[18]
J. S. B. Mitchell, Approximating watchman routes, Proc. 24th ACM-SIAM Sympos. Discrete Algo., 2013, pp. 844--855.
[19]
J. O'Rourke, Art Gallery Theorems and Algorithms, Oxford University Press, 1987.
[20]
M. Rao, G. Dudek, and S. Whitesides, Minimum distance localization for a robot with limited visibility, Proc. IEEE Intl. Conf. Robotics Automat., 2005, pp. 2438--2445.
[21]
H. Samet, Foundations of Multidimensional and Metric Data Structures, Morgan Kaufmann, 2005.
[22]
S. Shekhar and S. Chawla, Spatial Databases: A Tour, Prentice Hall, 2003.
[23]
T. Siméon, J.-P. Laumond, and C. Nissoux, Visibility-based probabilistic roadmaps for motion planning, Advanced Robotics, 14 (2000), 477--493.
[24]
K. R. Varadarajan and P. K. Agarwal, Approximating shortest paths on a nonconvex polyhedron, SIAM J. Comput., 30 (2000), 1321--1340.
[25]
Wikipedia. Art gallery problem --- wikipedia, the free encyclopedia, 2013. {Online; accessed 1-July-2013}.
[26]
C. Zheng, H. Yin, J. Li, and M. Lu, A particle swarm optimization algorithm for least visual path problem in raster terrain, Proc. Intl. Conf. Intell. Comput. Bio-Medical Instr., 2011, 228--231.

Cited By

View all
  • (2018)An Efficient Algorithm for Computing High-Quality Paths amid Polygonal ObstaclesACM Transactions on Algorithms10.1145/323065014:4(1-21)Online publication date: 21-Aug-2018
  • (2017)Optimal Aircraft Planar Navigation in Static Threat EnvironmentsIEEE Transactions on Aerospace and Electronic Systems10.1109/TAES.2017.269660353:5(2413-2426)Online publication date: Oct-2017
  • (2016)An efficient algorithm for computing high-quality paths amid polygonal obstaclesProceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete algorithms10.5555/2884435.2884517(1179-1192)Online publication date: 10-Jan-2016
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
SIGSPATIAL'13: Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 2013
598 pages
ISBN:9781450325219
DOI:10.1145/2525314
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

In-Cooperation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2013

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. GIS
  2. navigation
  3. terrain modeling
  4. visibility

Qualifiers

  • Research-article

Funding Sources

Conference

SIGSPATIAL'13
Sponsor:

Acceptance Rates

Overall Acceptance Rate 257 of 1,238 submissions, 21%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 05 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2018)An Efficient Algorithm for Computing High-Quality Paths amid Polygonal ObstaclesACM Transactions on Algorithms10.1145/323065014:4(1-21)Online publication date: 21-Aug-2018
  • (2017)Optimal Aircraft Planar Navigation in Static Threat EnvironmentsIEEE Transactions on Aerospace and Electronic Systems10.1109/TAES.2017.269660353:5(2413-2426)Online publication date: Oct-2017
  • (2016)An efficient algorithm for computing high-quality paths amid polygonal obstaclesProceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete algorithms10.5555/2884435.2884517(1179-1192)Online publication date: 10-Jan-2016
  • (2016)TerraNNIACM Transactions on Spatial Algorithms and Systems10.1145/27867572:2(1-31)Online publication date: 21-Jun-2016
  • (2014)Parallel multiple observer siting on terrainProceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/2666310.2666486(489-492)Online publication date: 4-Nov-2014
  • (2014)Computing highly occluded paths using a sparse networkProceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/2666310.2666394(3-12)Online publication date: 4-Nov-2014

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media