Efficient algorithms for pursuing moving evaders in terrains

Alon Efrat, Joseph S B Mitchell, Swaminathan Sankararaman, Parrish Myers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We propose algorithms for computing optimal trajectories of a group of flying observers (such as helicopters or UAVs) searching for a lost child in a hilly terrain. Very few assumptions are made about the speed or direction of the child's motion and whether it might (either deliberately or accidentally) try to avoid being found. This framework can also be applied to seekers searching for hostile evaders, such as smugglers/criminals, or friendly evaders, such as lost hikers. Based on the features of the area of the terrain where the pursuit takes place, and the visibility and motion characteristics of the UAVs, we show how to plan their synchronized trajectories in a way that maximizes the likelihood of a successful pursuit, while minimizing their battery or fuel usage, which may, in turn, enable a longer pursuit. Our algorithm explores useful I/O-efficient data structures and branch-cutting (search pruning) techniques to achieve further speedup by limiting the storage requirements and the total number of graph nodes searched, respectively.

Original languageEnglish (US)
Title of host publicationGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
Pages33-42
Number of pages10
DOIs
StatePublished - 2012
Event20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012 - Redondo Beach, CA, United States
Duration: Nov 6 2012Nov 9 2012

Other

Other20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012
CountryUnited States
CityRedondo Beach, CA
Period11/6/1211/9/12

Fingerprint

Pursuit
Unmanned aerial vehicles (UAV)
Efficient Algorithms
trajectory
Trajectories
pruning
Helicopters
Visibility
visibility
Data structures
Optimal Trajectory
Motion
Helicopter
Pruning
Battery
Observer
Likelihood
Data Structures
Speedup
Branch

Keywords

  • algorithms
  • branch-cutting
  • coordinated route planning
  • I/O-efficient data structures
  • search and rescue
  • sensors
  • UAV

ASJC Scopus subject areas

  • Earth-Surface Processes
  • Computer Science Applications
  • Modeling and Simulation
  • Computer Graphics and Computer-Aided Design
  • Information Systems

Cite this

Efrat, A., Mitchell, J. S. B., Sankararaman, S., & Myers, P. (2012). Efficient algorithms for pursuing moving evaders in terrains. In GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems (pp. 33-42) https://doi.org/10.1145/2424321.2424327

Efficient algorithms for pursuing moving evaders in terrains. / Efrat, Alon; Mitchell, Joseph S B; Sankararaman, Swaminathan; Myers, Parrish.

GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2012. p. 33-42.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Efrat, A, Mitchell, JSB, Sankararaman, S & Myers, P 2012, Efficient algorithms for pursuing moving evaders in terrains. in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. pp. 33-42, 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012, Redondo Beach, CA, United States, 11/6/12. https://doi.org/10.1145/2424321.2424327
Efrat A, Mitchell JSB, Sankararaman S, Myers P. Efficient algorithms for pursuing moving evaders in terrains. In GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2012. p. 33-42 https://doi.org/10.1145/2424321.2424327
Efrat, Alon ; Mitchell, Joseph S B ; Sankararaman, Swaminathan ; Myers, Parrish. / Efficient algorithms for pursuing moving evaders in terrains. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2012. pp. 33-42
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