Search and pursuit-evasion in mobile robotics A survey

Autonomous Robots

Volumn 31, Issue 4, 2011, Pages 299-316

  Chung, Timothy H ^a   Hollinger, Geoffrey A ^b   Isler, Volkan ^c  

^a Naval Postgraduate School   (United States)

^b University of Southern California   (United States)

^c University of Minnesota   (United States)

Author keywords

Autonomous search; Pursuit evasion; Search theory

Indexed keywords

AUTONOMOUS SEARCH; FIELD IMPLEMENTATION; MOBILE ROBOTIC; MOBILE ROBOTIC SYSTEMS; OPEN PROBLEMS; PROBABILISTIC SEARCH; PURSUIT-EVASION; SEARCH PROBLEM; SEARCH THEORY;

DIGITAL FILTERS; ROBOTICS; ROBOTS; SURVEYS;

NAVIGATION;

EID: 84555191194     PISSN: 09295593     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10514-011-9241-4     Document Type: Review

References (84)

1. Adler, M., Räcke, H., Sivadasan, N., Sohler, C., and Vöcking, B. (2003). Randomized pursuit-evasion in graphs. Combinatorics, Probability & Computing, 12(3), 225-244.
2. Aigner, M., and Fromme, M. (1984). A game of cops and robbers. Discrete Applied Mathematics, 8(1), 1-12.
3. Alexander, S., Bishop, R., and Ghrist, R. (2006). Pursuit and evasion in non-convex domains of arbitrary dimensions. In Proc. robotics: Science and systems conference.
4. Alexander, S., Bishop, R., and Ghrist, R. (2009). Capture pursuit games on unbounded domains. L'Enseignement Mathématique, 55, 103-125.
5. Alonso, L., Goldstein, A. S., and Reingold, E. M. (1992). Lion and man: Upper and lower bounds. INFORMS Journal on Computing, 4(4), 447.
6. Alspach, B. (2004). Searching and sweeping graphs: A brief survey. Matematiche, 59, 5-37.
7. Assaf, D., and Zamir, S. (1985). Optimal sequential search: A Bayesian approach. Annals of Statistics, 13(3), 1213-1221.
8. Barrière, L., Fraigniaud, P., Santoro, N., and Thilikos, D. (2003). Searching is not jumping, graph-theoretic concepts in computer. Science, 2880, 34-45.
9. Ba̧sar, T., and Olsder, G. J. (1999). Dynamic noncooperative game theory. Philadelphia: Society for Industrial Mathematics.
10. Benkoski, S. J., Monticino, M. G., &Weisinger, J. R. (1991). A survey of the search theory literature. Naval Research Logistics, 38(4), 469-494.
11. Bhadauria, D., and Isler, V. (2011). Capturing an evader in a polygonal environment with obstacles. In Proc. international joint conference on artificial intelligence.
12. Bhattacharya, S., and Hutchinson, S. (2010). On the existence of Nash equilibrium for a visibility based pursuit evasion game. The International Journal of Robotics Research, 29(7), 831-839.
13. Bienstock, D., and Seymour, P. D. (1991). Monotonicity in graph searching. Journal of Algorithms, 12(2), 239-245.
14. Bopardikar, S. D., Bullo, F., and Hespanha, J. P. (2007). Sensing limitations in the Lion and Man problem. In Proc. American control conference (pp. 5958-5963).
15. Borie, R., Tovey, C., and Koenig, S. (2009). Algorithms and complexity results for pursuit-evasion problems. In Proc. international joint conference on artificial intelligence (pp. 59-66).
16. Bourgault, F., Furukawa, T., and Durrant-Whyte, H. F. (2003). Coordinated decentralized search for a lost target in a Bayesian world. In Proc. IEEE/RSJ international conference on intelligent robots and systems (pp. 48-53).
17. Bourgault, F., Furukawa, T., and Durrant-Whyte, H. F. (2006). Optimal search for a lost target in a Bayesian world. Field and Service Robotics, 24, 209-222. (Pubitemid 44430500)
18. Chew, M. C. (1967). A sequential search procedure. Annals of Mathematical Statistics, 38(2), 494-502.
19. Chew, M. C., and Milton, C. (1973). Optimal stopping in a discrete search problem. Operations Research, 21(3), 741-747.
20. Dambreville, F., and Cadre, J. P. L. (2002). Search game for a moving target with dynamically generated informations. In Proc. international conference on information fusion (pp. 243-250).
21. Dobbie, J. M. (1968). A survey of search theory. Operations Research, 16(3), 525-537.
22. Dobbie, J. M. (1973). Some search problems with false contacts. Operations Research, 21(4), 907-925.
23. Eagle, J. N., and Yee, J. R. (1990). An optimal branch-and-bound procedure for the constrained path, moving target search problem. Operations Research, 38(1), 110-114.
24. Eaton, J., and Zadeh, L. (1962). Optimal pursuit strategies in discretestate probabilistic systems. Journal of Basic Engineering, 84, 23-28.
25. Fomin, F. V., and Thilikos, D. M. (2008). An annotated bibliography on guaranteed graph searching. Theoretical Computer Science, 399(3), 236-245.
26. Gerkey, B., Thrun, S., and Gordon, G. (2005). Parallel stochastic hillclimbing with small teams. In Proc. international NRL workshop on multi-robot systems.
27. Goldstein, A. S., and Reingold, E. M. (1995). The complexity of pursuit on a graph. Theoretical Computer Science, 143(1), 93-112.
28. Goodrich, M., Morse, B., Gerhardt, D., Cooper, J., Quigley, M., Adams, J., and Humphrey, C. (2008). Supporting wilderness search using a camera-equipped UAV. Journal of Field Robotics, 25(1-2), 89-110. (Pubitemid 351144574)
29. Guibas, L., Latombe, J., LaValle, S., Lin, D., and Motwani, R. (1999). Visibility-based pursuit-evasion in a polygonal environment. International Journal of Computational Geometry and Applications, 9(5), 471-494.
30. Hespanha, J., Prandini, M., and Sastry, S. (2000). Probabilistic pursuitevasion games: A one-step Nash approach. In Proc. IEEE conference on decision and control (pp. 2272-2277). (Pubitemid 32528370)
31. Hohzaki, R. (2007). Discrete search allocation game with false contacts. Naval Research Logistics, 54(1), 46-58. (Pubitemid 46191314)
32. Hollinger, G., Singh, S., Djugash, J., and Kehagias, A. (2009). Efficient multi-robot search for a moving target. The International Journal of Robotics Research, 28(2), 201-219.
33. Hollinger, G., Kehagias, A., and Singh, S. (2010a). GSST: Anytime guaranteed search. Autonomous Robots, 29(1), 99-118.
34. Hollinger, G., Kehagias, A., and Singh, S. (2010b). Improving the efficiency of clearing with multi-agent teams. The International Journal of Robotics Research, 29(8), 1088-1105.
35. Isler, V., and Karnad, N. (2008). The role of information in the coprobber game. Theoretical Computer Science, 3(399), 179-190 Special issue on graph searching.
36. Isler, V., Kannan, S., and Khanna, S. (2005). Randomized pursuitevasion in a polygonal environment. IEEE Transactions on Robotics, 21(5), 875-884.
37. Isler, V., Kannan, S., and Khanna, S. (2006). Randomized pursuitevasion with local visibility. SIAM Journal on Discrete Mathematics, 1(20), 26-41.
38. Jankovic, V. (1978). About a man and lions. Matemati?cki Vesnik, 2, 359-361.
39. Kadane, J. (1971). Optimal whereabouts search. Operations Research, 19(4), 894-904.
40. Kalbaugh, D. (1992). Optimal search among false contacts. SIAM Journal on Applied Mathematics, 52(6), 1722-1750. (Pubitemid 23586487)
41. Karnad, N., and Isler, V. (2008). Bearing-only pursuit. In Proc. IEEE international conference on robotics and automation (pp. 2665-2670).
42. Katsilieris, F., Lindhé, M., Dimarogonas, D., Ögren, P., and Johansson, K. (2010). Demonstration of multi-robot search and secure. In Proc. ICRA workshop on search and pursuit/evasion.
43. Kimeldorf, G., and Smith, F. (1979). Binomial searching for a random number of multinomially hidden objects. Management Science, 25(11), 1115-1126.
44. Kolling, A., and Carpin, S. (2010). Pursuit-evasion on trees by robot teams. IEEE Transactions on Robotics, 26(1), 32-47.
45. Kolling, A., Kleiner, A., Lewis, M., and Sycara, K. (2010). Pursuitevasion in 2.5D based on team-visibility. In Proc. IEEE/RSJ international conference on intelligent robots and systems (pp. 4610-4616).
46. Kolling, A., Kleiner, A., Lewis, M., and Sycara, K. (2011). Computing and executing strategies for moving target search. In Proc. IEEE international conference on robotics and automation (pp. 4246-423).
47. Koopman, B. O. (1956a). The theory of search. Part I. Kinematic bases. Operations Research, 4(5), 324-346.
48. Koopman, B. O. (1956b). The theory of search. Part II. Target detection. Operations Research, 4(5), 503-531.
49. Koopman, B. O. (1957). The theory of search. Part III. The optimum distribution of searching effort. Operations Research, 5(5), 613-626.
50. Koopman, B. O. (1979). Search and its optimization. The American Mathematical Monthly, 86(7), 527-540.
51. Kopparty, S., and Ravishankar, C. V. (2005). A framework for pursuit evasion games in Rn. Information Processing Letters, 96(3), 114-122.
52. Kress, M., Lin, K. Y., and Szechtman, R. (2008). Optimal discrete search with imperfect specificity. Mathematical Methods of Operations Research, 68(3), 539-549.
53. LaPaugh, A. S. (1993). Recontamination does not help to search a graph. Journal of the Association for Computing Machinery, 40(2), 224-245.
54. Lau, H., Huang, S., and Dissanayake, G. (2005). Optimal search for multiple targets in a built environment. In Proc. IEEE/RSJ international conference on intelligent robots and systems (pp. 3740-3745).
55. Lau, H., Huang, S., and Dissanayake, G. (2006). Probabilistic search for a moving target in an indoor environment. In Proc. IEEE/RSJ international conference on intelligent robots and systems (pp. 3393-3398). (Pubitemid 46928432)
56. LaValle, S. M. (2006). Planning algorithms. Cambridge: Cambridge University Press.
57. LaValle, S., Lin, D., Guibas, L., Latombe, J., and Motwani, R. (1997). Finding an unpredictable target in a workspace with obstacles. In Proc. IEEE international conference on robotics and automation (pp. 737-742).
58. Lazebnik, S. (2001). Visibility-based pursuit-evasion in threedimensional environments. Technical report, CVR-TR-2001-01, Beckman Institute, University of Illinois at Urbana-Champaign.
59. Lenstra, J. K., and Kan, A. H. G. R. (1981). Complexity of vehicle routing and scheduling problems. Networks, 11(2), 221-227. (Pubitemid 13506973)
60. Littlewood, J. E. (1953). A mathematician's miscellany. London: Methuen & Co.
61. McCue, B. (1990). U-boats in the bay of Biscay: An essay in operations analysis. National Defense University Press.
62. Megiddo, N., Hakimi, S., Garey, M., Johnson, D., and Papadimitriou, C. (1988). The complexity of searching a graph. Journal of the Association for Computing Machinery, 35(1), 18-44.
63. Murrieta-Cid, R., Muppirala, T., Sarmiento, A., Bhattacharya, S., & Hutchinson, S. (2007). Surveillance strategies for a pursuer with finite sensor range. The International Journal of Robotics Research, 26(3), 233-253. (Pubitemid 46353955)
64. Nowakowski, R., and Winkler, P. (1983). Vertex-to-vertex pursuit in a graph. Discrete Mathematics, 43(2-3), 235-239.
65. Ong, S. C. W., Png, S. W., Hsu, D., and Lee, W. S. (2010). Planning under uncertainty for robotic tasks with mixed observability. The International Journal of Robotics Research, 29(8), 1053-1068.
66. Park, S.-M., Lee, J.-H.,&Chwa, K.-Y. (2001). Visibility-based pursuitevasion in a polygonal region by a searcher. In Proc. international colloquium on automata, languages and programming (pp. 456-468). (Pubitemid 33300821)
67. Parsons, T. (1976). Pursuit-evasion in a graph. In Y. Alavi & D. Lick (Eds.), Theory and applications of graphs (pp. 426-441). Berlin: Springer.
68. Ross, S. M. (1969). A problem in optimal search and stop. Operations Research, 17(6), 984-992.
69. Roy, N., Gordon, G., and Thrun, S. (2005). Finding approximate POMDP solutions through belief compression. The Journal of Artificial Intelligence Research, 23, 1-40. (Pubitemid 41525865)
70. Sato, H., and Royset, J. O. (2010). Path optimization for the resourceconstrained searcher. Naval Research Logistics, 57(5), 422-440.
71. Sgall, J. (2001). Solution of David Gale's lion and man problem. Theoretical Computer Science, 259(1-2), 663-670. (Pubitemid 32674048)
72. Stone, L. D. (1989a). Theory of optimal search (2nd edn.). San Diego: Academic Press.
73. Stone, L. D. (1989b).What's happened in search theory since the 1975 Lanchester prize? Operations Research, 37(3), 501-506.
74. Tisdale, J., Kim, Z., and Hedrick, J. K. (2009). Autonomous path planning and estimation using UAVs. IEEE Robotics & Automation Magazine, 16(2), 35-42.
75. Toth, P., and Vigo, D. (2002). The vehicle routing problem. Philadelphia: Society for Industrial Mathematics.
76. Trummel, K. E., and Weisinger, J. R. (1986). The complexity of the optimal searcher path problem. Operations Research, 34(2), 324-327. (Pubitemid 17461689)
77. Vidal, R., Shakernia, O., Kim, H. J., Shim, D. H., and Sastry, S. (2002). Probabilistic pursuit-evasion games: Theory, implementation, and experimental evaluation. IEEE transactions on robotics and automation, 18(5), 662-669.
78. Vieira, M., Govindan, R., and Sukhatme, G. S. (2009). Scalable and practical pursuit-evasion with networked robots. Journal of Intelligent Service Robotics, 2(4), 247-263.
79. Wagner, D. H. (1999). Naval operations analysis. Annapolis: United States Naval Institute.
80. Washburn, A. R. (1983). Search for a moving target: The FAB algorithm. Operations Research, 31(4), 739-751.
81. Washburn, A. R. (1998). Branch and bound methods for a search problem. Naval Research Logistics, 45(3), 243-257. (Pubitemid 128592885)
82. Washburn, A. R. (2002). Search and detection. Topics in operations research series (4th edn.) INFORMS.
83. Wegener, I. (1985). Optimal search with positive switch cost is NPhard. Information Processing Letters, 21(1), 49-52. (Pubitemid 15547374)
84. Wong, E.-M., Bourgault, F., and Furukawa, T. (2005). Multi-vehicle Bayesian search for multiple lost targets. In Proc. IEEE international conference on robotics and automation (pp. 3169-3174). (Pubitemid 46084273)