Introduction to algorithms
Efficiently searching a graph by a smell-oriented vertex process
Annals of Mathematics and Artificial Intelligence
Spanning-tree based coverage of continuous areas by a mobile robot
Annals of Mathematics and Artificial Intelligence
Coverage for robotics – A survey of recent results
Annals of Mathematics and Artificial Intelligence
Competitive on-line coverage of grid environments by a mobile robot
Computational Geometry: Theory and Applications
A Theoretical Analysis of Multi-Agent Patrolling Strategies
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Theoretical Analysis of the Multi-agent Patrolling Problem
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
An efficient heuristic approach for security against multiple adversaries
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
The impact of adversarial knowledge on adversarial planning in perimeter patrol
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
A realistic model of frequency-based multi-robot polyline patrolling
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
On redundancy, efficiency, and robustness in coverage for multiple robots
Robotics and Autonomous Systems
The giving tree: constructing trees for efficient offline and online multi-robot coverage
Annals of Mathematics and Artificial Intelligence
Multi-agent patrolling: an empirical analysis of alternative architectures
MABS'02 Proceedings of the 3rd international conference on Multi-agent-based simulation II
Uncertainties in adversarial patrol
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Ship patrol: multiagent patrol under complex environmental conditions
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Boundary patrolling by mobile agents with distinct maximal speeds
ESA'11 Proceedings of the 19th European conference on Algorithms
Multi-robot adversarial patrolling: facing a full-knowledge opponent
Journal of Artificial Intelligence Research
Near-optimal continuous patrolling with teams of mobile information gathering agents
Artificial Intelligence
Multi-robot repeated area coverage
Autonomous Robots
Optimal patrolling of fragmented boundaries
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
International Journal of Robotics Research
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
Patrolling involves generating patrol paths for mobile robots such that every point on the paths is repeatedly covered. This paper focuses on patrolling in closed areas, where every point in the area is to be visited repeatedly by one or more robots. Previous work has often examined paths that allow for repeated coverage, but ignored the frequency in which points in the area are visited. In contrast, we first present formal frequency-based optimization criteria used for evaluation of patrol algorithms. Then, we present a patrol algorithm that guarantees maximal uniform frequency, i.e., each point in the target area is covered at the same optimal frequency. This solution is based on finding a circular path that visits all points in the area, while taking into account terrain directionality and velocity constraints. Robots are positioned uniformly along this path in minimal time, using a second algorithm. Moreover, the solution is guaranteed to be robust in the sense that uniform frequency of the patrol is achieved as long as at least one robot works properly. We then present a set of algorithms for handling events along the patrol path. The algorithms differ in the way they handle the event, as a function of the time constraints for handling them. However, all the algorithms handle events while maintaining the patrol path, and minimizing the disturbance to the system.