SmartSwarms: Distributed UAVs that Think

Abstract

Unmanned Aerial Vehicles (UAVs) have demonstrated tremendous capability in recent military operations. Recently swarm technology has been suggested as a possible solution to automatically control and coordinate multiple UAVs. The idea behind a swarm is that simple local rules that govern the behavior of individual entities can lead to complex emergent behavior of the system as a whole. Although such systems have achieved limited success in simulated applications, finding good rules can be difficult for humans. Moreover, such rules can result in odd behavior or unnecessarily long missions. This paper describes a swarm-based multi-UAV system, called SmartSwarms, using a radically different approach: instead of operating with human-defined rules, each individual reasons using Simulated LookAhead (SLA), thus incorporating a model of its world and nearby entities in decision-making. Our results show that this approach can improve swarm behavior in UAVs. SLA is affordable, scalable to a large number of UAVs, deconflicts in real-time, learns over time, is interoperable, reusable, fault tolerant, and error tolerant, and can handle uncertainty.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2004
Accession Number
ADA465279

Entities

People

  • Andrew Arcilla
  • Armand Prieditis
  • Brett Groel
  • Michael Van Der Bock
  • Mukesh Dalal
  • Richard Kong

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Control Systems
  • Decision Theory
  • Genetic Algorithms
  • Military Applications
  • Military Operations
  • Neural Networks
  • Rotary Wing Aircraft
  • Simulations
  • Standards
  • Swarming Technologies
  • Two Dimensional
  • Unmanned Aerial Vehicles
  • Unmanned Ground Vehicles
  • Unmanned Vehicles
  • Vehicles

Fields of Study

  • Computer science

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Applied Combinatorial Optimization and Logic Circuit Design.

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control
  • Autonomy - UAVs