Crawler Control Strategies and Their Influence on Mine Finding Capabilities

Abstract

Autonomous underwater vehicles (AUVs) have found a permanent application doing mine countermeasures (MCM). Autonomous crawlers can be used to perform mine search patterns, but in doing so can encounter many problems, one of which is obstacles. For a crawler, knowing how to avoid obstacles and what to do after avoiding obstacles is important to performing searches quickly and effectively. A fuzzy logic controller was developed to perform a comparison between point to point control and trajectory control with mine finding capability being the basis for comparison. A random walk control method was also simulated to show how it compared to the other methods. Search times were found to be similar, but the trajectory control was found to be more reliable at finding a larger percentage of mines. The trajectory control was optimized to more closely follow the trajectory and a comparison was performed between the baseline and optimized trajectory controls. After optimization, the crawler was able to stay on a straight line path for a larger percentage of the search time. This resulted in better mine finding performance than the preoptimization trajectory control.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA459055

Entities

People

  • Dean B. Edwards
  • Douglas M. Welling

Organizations

  • University of Idaho

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Autonomous Underwater Vehicles
  • Autonomous Vehicles
  • Collision Avoidance
  • Fuzzy Logic
  • Logic
  • Military Organizations
  • Monte Carlo Method
  • Navy
  • Optimization
  • Probability
  • Random Walk
  • Side Looking Sonar
  • Simulations
  • Standards
  • Trajectories
  • Vehicles

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Naval Mine Countermeasure Systems Development.
  • Robotics and Automation.