An Artificial Neural System for Autonomous Undersea Vehicles

Abstract

This paper introduces a new approach to the problem of information processing in autonomous undersea vehicles (AUVs). The approach involves the emulation of biological mechanisms of intelligence, principally through the evolutionary design of neural networks and systems of interacting networks, for implementation in software, parallel hardware, and analog/digital very-large- scale integration (VLSI). The objectives of artificial neural systems (ANS), in common with other AI approaches, are to provide real-time, operator-independent, pattern recognition, task planning, and adaptive AUV control for many of the underwater tasks currently being performed by man. The ANS approach emphasizes the development of autonomous intelligence capabilities through the progressive expansion of processing centers that define, orchestrate, and control basic reflexes. Keywords: Artificial neural systems; Autonomous undersea vehicles; Neural networks.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1988
Accession Number
ADA199725

Entities

People

  • H. G. Nguyen
  • M. R. Blackburn

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Sensors

DTIC Thesaurus Topics

  • Autonomous Underwater Vehicles
  • Brain
  • C Programming Language
  • Cells
  • Computer Programming
  • Computer Vision
  • Computers
  • Control Systems
  • Data Processing
  • Detectors
  • Engineering
  • Image Processing
  • Nervous System
  • Oceans
  • Pattern Recognition
  • Recognition
  • Simulations

Readers

  • Neural Network Machine Learning.
  • Software Engineering.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks