Automating Barrier Assessment with Mobile Security Robots

Abstract

Barrier assessment is the time consuming and labor-intensive process of manual inspection of locks on doors and gates by security guards. The Mobile Detection Assessment Response System (MDARS) uses Unmanned Ground Vehicles (UGVs) and a Barrier Assessment System (BAS) to automate lock inspection and report an unsecured area to the security force thereby improving their ability to detect and respond to unauthorized access. MDARS is adjoint U.S. Army-Navy development effort to field mobile robots at Department of Defense (DoD) sites for physical security and automated inventory missions. MDARS UGVs patrol autonomously outside of storage facilities and operate payloads for intruder detection, inventory assessment, and barrier assessment. For barrier assessment, the robots remotely monitor the status of locks with Internal Locking Devices. The robot will notify the user if a lock is opened or has been compromised. This paper details the evolution of the BAS from prototype design to successfully passing developmental testing. Additional emphasis is placed on integration of the barrier assessment payload with the MDARS Exterior robot, installation of the BAS support equipment in a storage area, user interface, and overall system improvements at an MDARS operational site.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2003
Accession Number
ADA422125

Entities

People

  • Daniel Carroll
  • Doriann Jaffee
  • Katherine Mullens

Organizations

  • Naval Information Warfare Systems Command

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Autonomous Navigation
  • Collision Avoidance
  • Command And Control
  • Department Of Defense
  • Detection
  • Detectors
  • Ground Vehicles
  • Intrusion Detection
  • Physical Security
  • Security
  • Security Personnel
  • Unmanned Ground Systems
  • Unmanned Ground Vehicles
  • Unmanned Systems
  • Unmanned Vehicles
  • Vehicles
  • Warning Systems

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Facility/Structural Engineering.

Technology Areas

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