Modeling, Analysis, and Control of Swarming Agents in a Probabilistic Framework

Abstract

This research effort focuses on the development of a unified, systematic, and formal approach to modeling and control of multi-agent systems, drawing inspiration from biological systems exhibiting swarm behavior. Previously developed works in the application of graph theory were further advanced and applied to a variety of different task-oriented multi-agent systems. New distributed on-board controllers were developed and implemented at the individual level, yielding collective results in exploration, perimeter detection and surveillance, and formation control that are indistinguishable from similar centrally controlled systems. This distributed control yields robustness and decreased complexity relative to centralized controllers. Simulations and experiments were conducted to validate the analytically obtained results. The major outcomes of this research have been published in a large number of peer-reviewed conference proceedings and scientific journal articles. The financial support provided by the Army Research Office to carry out this research has been duly acknowledged in these articles.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2012
Accession Number
ADA583926

Entities

People

  • Devendra P. Garg
  • Gregory K. Fricke

Organizations

  • Duke University

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Cell Movement
  • Cells
  • Cognitive Systems Engineering
  • Collision Avoidance
  • Computational Science
  • Computer Programming
  • Control Systems
  • Information Science
  • Lymphatic System
  • Lymphocytes
  • Medical Personnel
  • Network Protocols
  • Network Science
  • Robotic Swarms
  • Robots
  • Three Dimensional
  • Two Dimensional

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Robotics and Automation.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control