Investigating Ground Swarm Robotics Using Agent Based Simulation

Abstract

The concept of employing ground swarm robotics to accomplish tasks has been proposed for future use in humanitarian de-mining, plume monitoring, searching for survivors in a disaster site, and other hazardous activities. More importantly in the military context, with the development of advanced explosive detectors, swarm robotics with autonomous search and detection capability could potentially address the improvised explosive device (IED) problem faced by foot patrols, and aid in the search for hidden ammunition caches and weapons of mass destruction (WMDs). The intent of this research is to leverage on agent based simulation to model a ground robotic swarm on a search and detection mission in a semi-urban environment rigged with stationary IEDs. Efficient design of experiment (DOE) techniques and data farming are engaged to help identify controllable factors and capabilities that have the most impact on overall effectiveness. The focus of this thesis is to explore agent based simulation applied to swarm robotics; the technological and algorithmic aspects are not delved on. Results from the simulations provide several insights on the impact of both decision and noise factors on the performance of the swarm. Incorporation of virtual pheromones as a shared memory map is modeled as an additional capability that is found to enhance the robustness and reliability of the swarm.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2006
Accession Number
ADA462523

Entities

People

  • Sze-tek T. Ho

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Collision Avoidance
  • Computer Programming
  • Defense Systems
  • Detection
  • Detectors
  • Experimental Design
  • Improvised Explosive Devices
  • Information Science
  • Knowledge Management
  • Munitions
  • Reliability
  • Robotic Swarms
  • Statistical Analysis
  • Unmanned Ground Vehicles
  • Unmanned Systems
  • Unmanned Vehicles
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

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