Sonar Localization of an Autonomous Underwater Vehicle

Abstract

Two different algorithms to navigate an AUV within a charted environment are presented. They use sonar returns and a local map together with the dynamic model to estimate the vehicle's position and acceleration at all times. Kalman filtering techniques are used to compute the estimates. The main difficulty is the presence of uncharted obstacles, which are identified by the potential function algorithm. Results show that first algorithm works in an environment without obstacles. Results from the application of the potential function algorithm in a pool using Tritech ST725 high resolution sonar show the feasibility and robustness of the potential function approach to the navigation problem.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1993
Accession Number
ADA276254

Entities

People

  • Enis Percin

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Autonomous Navigation
  • Autonomous Underwater Vehicles
  • Collision Avoidance
  • Computational Science
  • Computer Programs
  • Computers
  • Engineering
  • Estimators
  • Guidance
  • Kalman Filters
  • Linear Systems
  • Motion Planning
  • Navigation
  • Navigators
  • Robot Navigation
  • Robots
  • Underwater Vehicles

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Oceanography.
  • Robotics and Automation.