Multi-Agent Simulations (MAS) for Assessing Massive Sensor Coverage and Deployment

Abstract

The thesis presents the design, development, and implementation of a multi-agent simulation that models coverage and deployment of mobile and non-mobile sensors performing collaborative target-detection missions. The focus is on sensor networks with enough sensors that humans cannot individually manage each sensor. Experiments investigate novel search, coverage, and deployment algorithms, and compare them to known methods. The experiments show algorithms productive for area coverage are not useful for detecting unauthorized traversals and vice versa. Obstacles, sensor mechanisms, mission parameters, and deployment schemes are analyzed for their effect on coverage quality. This work facilitates further research in sensor coverage and deployment strategies using sensor agents.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2003
Accession Number
ADA418620

Entities

People

  • Sean Hynes

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Collision Avoidance
  • Computer Networks
  • Computer Programming
  • Computers
  • Detectors
  • Energy Consumption
  • Mesh Networks
  • Motion Planning
  • Network Science
  • Neural Networks
  • Robots
  • Sensor Networks
  • Wireless Communications
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Sensor Fusion and Tracking Systems.
  • Software Engineering.