Local Navigation for Unmanned Group Vehicles

Abstract

This document surveys existing methods of local navigation of mobile robots. It analyzes the state of the art in both indoor obstacle avoidance techniques and those for outdoor rough terrain. A variety of techniques such as Potential Fields, Vector Field Histogram, and Dynamic Window are examined in detail, in addition to outdoor systems such as Ranger, Morphin and the NIST Demo III architecture. Finally, it discusses the applicability of robot motion planning algorithms like Rapidly Exploring Random Trees to the robot navigation problem.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2005
Accession Number
ADA605022

Entities

People

  • Jared L. Giesbrecht

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Algorithms
  • Autonomous Navigation
  • Autonomous Systems
  • Classification
  • Collision Avoidance
  • Computational Science
  • Control Systems
  • Guidance
  • Motion Planning
  • Navigation
  • Navigators
  • Robot Navigation
  • Robotics
  • Robots
  • Three Dimensional
  • Two Dimensional
  • Unmanned Ground Vehicles

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy