Robotic Navigation in GPS-Denied Environments Using the Strapdown Navigation Algorithm with Zero-Velocity Updates

Abstract

GPS-denied environments, including indoor, urban canyon, and shipboard settings, present difficulties for autonomous robot navigation. One navigation solution in GPS-denied environments is to incorporate inertial sensors; however, due to sensor noise and calibration error, the accumulation of position error, or drift, causes the position estimate from inertial sensors to fail after a period of time. This thesis aimed to determine the viability of a pedestrian algorithm, which incorporates the zero-velocity update, to address the error and calculate distance traveled by a mobile robot in a GPS-denied environment. This work focused on indoor navigation using various sensors to provide data to the algorithm to calculate estimated distance traveled. Experiments were constructed and performed using a cart, robot, and mounted sensors in three laboratory settings: across the ground with preset distances, on an instrument rail track, and in an optical tracking environment. Tests conducted with the sensors determined that a system traveling above a minimum velocity threshold up to three meters can effectively implement a pedestrian tracking algorithm given known quaternion values. Adding a native means of determining system angles will allow this solution to be applied in more environments.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2020
Accession Number
AD1114558

Entities

People

  • Samuel S. Druen

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Angular Motion
  • Artificial Intelligence
  • Autonomous Navigation
  • Autonomous Systems
  • Collision Avoidance
  • Computers
  • Coordinate Systems
  • Global Positioning Systems
  • Graphical User Interface
  • Guidance
  • Inertial Measurement Units
  • Inertial Navigation
  • Inertial Navigation Systems
  • Measurement
  • Navigation
  • Neural Networks
  • Robot Navigation
  • Robots
  • World Geodetic System

Readers

  • Inertial Navigation Systems.
  • Robotics and Automation.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Space