1 / 1

Ship Patrol: Multiagent Patrol under Complex Environmental Conditions

Ship Patrol: Multiagent Patrol under Complex Environmental Conditions. Full paper to appear in AAAI’11. Noa Agmon, Daniel Urieli and Peter Stone Department of Computer Science The University of Texas at Austin {agmon, urieli, pstone }@ cs.utexas.edu.

rania
Télécharger la présentation

Ship Patrol: Multiagent Patrol under Complex Environmental Conditions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Ship Patrol: Multiagent Patrol under Complex Environmental Conditions Full paper to appear in AAAI’11 Noa Agmon, Daniel Urieli and Peter Stone Department of Computer Science The University of Texas at Austin {agmon, urieli, pstone}@cs.utexas.edu Multiagent Frequency-Based Graph Patrol Problem: Team of k agents should repeatedly visit nodes of graph G=(V,E) while minimizing idleness at each node Current Strategies SingleCycle All agents travel in coordination along one cycle UniPartition V(G) divided into ksubgraphs, each agents patrols inside its subgraph Optimal strategy: Intractable Optimal strategy: Intractable Complex Environments New, General Strategy • Example: Marine Environments • Time of travel does not correspond to physical distance • Influenced by water currents, winds, waves • No triangle inequality → Cannot use common approximation algorithms MultiPartition V(G) divided into m≤ksubgraphs, with possibly more than one agent patrolling in each subgraph Current strategies are not necessarily suitable BiconnectedOuterplanar Graphs A cycle with non intersecting shortcuts MultiPartition Optimal Strategy Intractable Finding an optimal MultiPartition strategy that minimizes worst idleness in G is NP-Hard. Solving the problem in biconnectedouterplanar graphs is also intractable Use heuristic algorithm UTSeaSim Algorithm HeuristicDivide Custom-designed naval surface navigation simulator Realistic 2D physical models of marine environment and sea vessel Contains three modules: Sea Environment wind, currents, obstacles Ship physical properties, sensing and actuators Decision Making autonomous agent controlling the ship Examine all divisions of the given cycle into two or three cycles Choose division that improves and minimizes idleness Continue recursively with each cycle in the division Implemented in UTSeaSim Significantly improves idleness compared to: SingleCycle Trivial adjustments (SinglePatrition cannot be computed) Medium level of winds and currents

More Related