The Detection of Explosives using Robotic Crawlers

Abstract

Chemical sensing of explosives may allow differentiation between mines and other mine-like objects, especially if close proximity to the targets can be achieved. Robotic crawlers are well suited to achieve the required proximity and have added advantages, including stability on the bottom and station-keeping. We have performed initial tests with an explosive sensor mounted on crawlers and two types of targets containing real explosives. In the tests, the robot successfully detected both targets at significant distances. For the initial test, the crawler approached the target from a direction upcurrent of the target so that any chemical signature emanating from the target would be transported away from the sensor. No sensor response was noted in this case. The robot was then repositioned by executing a number of turns placing the robot and sensor downcurrent from the target. Shortly after arriving in this position, intermittent sensor responses were observed. These responses were similar to what is observed in the laboratory. The response to the targets was rapid and reversible. In order to gain insight into how most effectively to sample the area around mine-like objects, we are also simulating chemical orientation using spatial modeling and analysis tools.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2003
Accession Number
ADA498901

Entities

People

  • R. T. Arrieta

Organizations

  • Naval Surface Warfare Center

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Amplitude
  • Aquatic Organisms
  • Autonomous Vehicles
  • Chemical Detectors
  • Detection
  • Detectors
  • Dispersions
  • Explosive Charges
  • Explosives
  • Far Field
  • Field Tests
  • Materials
  • Orientation (Direction)
  • Probability
  • Simulations
  • Unmanned Vehicles
  • Vehicles

Readers

  • Acoustical Oceanography.
  • Mathematics or Statistics
  • Robotics and Automation.

Technology Areas

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