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An Efficient Solution to the 2D Visibility Problem in Cartesian Grid Maps and its Application in Heuristic Path Planning (2403.06494v1)

Published 11 Mar 2024 in cs.CG, cs.GR, and cs.RO

Abstract: This paper introduces a novel, lightweight method to solve the visibility problem for 2D grids. The proposed method evaluates the existence of lines-of-sight from a source point to all other grid cells in a single pass with no preprocessing and independently of the number and shape of obstacles. It has a compute and memory complexity of $\mathcal{O}(n)$, where $n = n_{x}\times{} n_{y}$ is the size of the grid, and requires at most ten arithmetic operations per grid cell. In the proposed approach, we use a linear first-order hyperbolic partial differential equation to transport the visibility quantity in all directions. In order to accomplish that, we use an entropy-satisfying upwind scheme that converges to the true visibility polygon as the step size goes to zero. This dynamic-programming approach allows the evaluation of visibility for an entire grid orders of magnitude faster than typical ray-casting algorithms. We provide a practical application of our proposed algorithm by posing the visibility quantity as a heuristic and implementing a deterministic, local-minima-free path planner, setting apart the proposed planner from traditional methods. Lastly, we provide necessary algorithms and an open-source implementation of the proposed methods.

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References (28)
  1. M. Bern and P. Plassmann, “Chapter 6 - mesh generation,” in Handbook of Computational Geometry, J.-R. Sack and J. Urrutia, Eds.   Amsterdam: North-Holland, 2000, pp. 291–332. [Online]. Available: https://www.sciencedirect.com/science/article/pii/B9780444825377500073
  2. L. S. Davis and M. Benedikt, “Computational models of space: Isovists and isovist fields,” Computer Graphics and Image Processing, vol. 11, pp. 49–72, 1979.
  3. B. Joe and R. B. Simpson, “Corrections to lee’s visibility polygon algorithm,” BIT Numerical Mathematics, vol. 27, pp. 458–473, 1987.
  4. T. Asano, T. Asano, L. J. Guibas, J. Hershberger, and H. Imai, “Visibility of disjoint polygons,” Algorithmica, vol. 1, pp. 49–63, 2005.
  5. P. J. Heffernan and J. S. B. Mitchell, “An optimal algorithm for computing visibility in the plane,” SIAM J. Comput., vol. 24, no. 1, p. 184–201, feb 1995. [Online]. Available: https://doi.org/10.1137/S0097539791221505
  6. F. Bungiu, M. Hemmer, J. Hershberger, K. Huang, and A. Kröller, “Efficient computation of visibility polygons,” ArXiv, vol. abs/1403.3905, 2014.
  7. L. Barba, M. Korman, S. Langerman, and R. I. Silveira, “Computing a visibility polygon using few variables,” Comput. Geom. Theory Appl., vol. 47, no. 9, p. 918–926, oct 2014.
  8. V. Chvátal, “A combinatorial theorem in plane geometry,” Journal of Combinatorial Theory, Series B, vol. 18, no. 1, pp. 39–41, 1975. [Online]. Available: https://www.sciencedirect.com/science/article/pii/0095895675900611
  9. M. E. Newell, R. G. Newell, and T. L. Sancha, “A solution to the hidden surface problem,” in Proceedings of the ACM Annual Conference - Volume 1, ser. ACM ’72.   New York, NY, USA: Association for Computing Machinery, 1972, p. 443–450. [Online]. Available: https://doi.org/10.1145/800193.569954
  10. P. Bose, A. Lubiw, and J. Munro, “Efficient visibility queries in simple polygons,” Computational Geometry, vol. 23, no. 3, pp. 313–335, 2002. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0925772101000700
  11. T. Lozano-Pérez and M. A. Wesley, “An algorithm for planning collision-free paths among polyhedral obstacles,” Commun. ACM, vol. 22, no. 10, p. 560–570, oct 1979. [Online]. Available: https://doi.org/10.1145/359156.359164
  12. M. Pocchiola and G. Vegter, “Topologically sweeping visibility complexes via pseudotriangulations,” Discrete & Computational Geometry, vol. 16, pp. 419–453, 1996.
  13. S. Kapoor and S. N. Maheshwari, “Efficiently constructing the visibility graph of a simple polygon with obstacles,” SIAM Journal on Computing, vol. 30, no. 3, pp. 847–871, 2000. [Online]. Available: https://doi.org/10.1137/S0097539795253591
  14. M. Kallmann, “Dynamic and robust local clearance triangulations,” ACM Trans. Graph., vol. 33, no. 5, sep 2014. [Online]. Available: https://doi.org/10.1145/2580947
  15. R. Zeng, Y. Wen, W. Zhao, and Y.-J. Liu, “View planning in robot active vision: A survey of systems, algorithms, and applications,” Computational Visual Media, vol. 6, no. 3, pp. 225–245, Sep 2020. [Online]. Available: https://doi.org/10.1007/s41095-020-0179-3
  16. K. Wu, R. Ranasinghe, and G. Dissanayake, “Active recognition and pose estimation of household objects in clutter,” in 2015 IEEE International Conference on Robotics and Automation (ICRA), 2015, pp. 4230–4237.
  17. C. McGreavy, L. Kunze, and N. Hawes, “Next best view planning for object recognition in mobile robotics,” in Proceedings of the 34th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG2016), Nov. 2016, 34th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG2016) ; Conference date: 15-12-2016 Through 16-12-2016.
  18. J. Santos, M. Oliveira, R. Arrais, and G. Veiga, “Autonomous scene exploration for robotics: A conditional random view-sampling and evaluation using a voxel-sorting mechanism for efficient ray casting,” Sensors, vol. 20, no. 15, 2020.
  19. B. Baker, I. Kanitscheider, T. M. Markov, Y. Wu, G. Powell, B. McGrew, and I. Mordatch, “Emergent tool use from multi-agent autocurricula,” in 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020.   OpenReview.net, 2020.
  20. A. Tandon and K. Karlapalem, “Medusa: Towards simulating a multi-agent hide-and-seek game,” in International Joint Conference on Artificial Intelligence, 2018.
  21. J. Amanatides and A. Woo, “A fast voxel traversal algorithm for ray tracing,” Proceedings of EuroGraphics, vol. 87, 08 1987.
  22. I. Ibrahim, F. Farshidian, J. Preisig, P. Franklin, P. Rocco, and M. Hutter, “Whole-body mpc and dynamic occlusion avoidance: A maximum likelihood visibility approach,” in 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 221–227.
  23. T. Nägeli, J. Alonso-Mora, A. Domahidi, D. Rus, and O. Hilliges, “Real-time motion planning for aerial videography with dynamic obstacle avoidance and viewpoint optimization,” IEEE Robotics and Automation Letters, vol. 2, no. 3, pp. 1696–1703, 2017.
  24. G. Allaire, M. Bihr, B. Bogosel, and M. Godoy, “Accessibility constraints in structural optimization via distance functions,” Nov. 2022, working paper or preprint. [Online]. Available: https://hal.science/hal-03864841
  25. R. Farias and M. Kallmann, “Optimal path maps on the gpu,” IEEE Transactions on Visualization and Computer Graphics, vol. 26, no. 9, pp. 2863–2874, 2020.
  26. H. Lewy, K. Friedrichs, and R. Courant, “Über die partiellen differenzengleichungen der mathematischen physik,” Mathematische Annalen, vol. 100, pp. 32–74, 1928. [Online]. Available: http://eudml.org/doc/159283
  27. D. Harabor and A. Grastien, “An optimal any-angle pathfinding algorithm,” in ICAPS 2013 - Proceedings of the 23rd International Conference on Automated Planning and Scheduling, 06 2013.
  28. T. Uras and S. Koenig, “An empirical comparison of any-angle path-planning algorithms,” in Symposium on Combinatorial Search, 2015.
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