Theoretical Computer Science
The complexity of searching a graph
Journal of the ACM (JACM)
Recontamination does not help to search a graph
Journal of the ACM (JACM)
Efficient and constructive algorithms for the pathwidth and treewidth of graphs
Journal of Algorithms
Capture of an intruder by mobile agents
Proceedings of the fourteenth annual ACM symposium on Parallel algorithms and architectures
Visibility-Based Pursuit-Evasion in a Polygonal Environment
WADS '97 Proceedings of the 5th International Workshop on Algorithms and Data Structures
Coordinated exploration of unknown labyrinthine environments applied to the pursuit evasion problem
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Visibility-based Pursuit-evasion with Limited Field of View
International Journal of Robotics Research
Planning Algorithms
An annotated bibliography on guaranteed graph searching
Theoretical Computer Science
Visibility-based pursuit-evasion with limited field of view
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Randomized pursuit-evasion in a polygonal environment
IEEE Transactions on Robotics
Delaunay refinement algorithms for triangular mesh generation
Computational Geometry: Theory and Applications
GSST: anytime guaranteed search
Autonomous Robots
Adaptive learning approach of fuzzy logic controller with evolution for pursuit-evasion games
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartI
Connected searching of weighted trees
Theoretical Computer Science
Algorithms and complexity results for graph-based pursuit evasion
Autonomous Robots
Hi-index | 0.98 |
Using concepts from both robotics and graph theory, we formulate the problem of indoor pursuit/evasion in terms of searching the nodes of a graph for a mobile evader. We present the IGNS (Iterative Greedy Node Search) algorithm, which performs offline guaranteed search (i.e. no matter how the evader moves, it will eventually be captured). Furthermore, the algorithm produces an internal search (the searchers move only along the edges of the graph; ''teleporting'' is not used) and exploits non-monotonicity, extended visibility and finite evader speed to reduce the number of searchers required to clear an environment. We present search experiments for several indoor environments, in all of which the algorithm succeeds in clearing the graph (i.e. capturing the evader).