A 3D State Space Formulation of a Navigation Kalman Filter for Autonomous Vehicles

Abstract

The Kalman Filter has many applications in mobile robotics ranging from perception, to position estimation, to control. This report formulates a navigation Kalman Filter. That is, one which estimates the position of autonomous vehicles. The filter is developed according-to the state space formulation of Kalman's original papers. The state space formulation is particularly appropriate for the problem of vehicle position estimation. This filter formulation is fairly general. This generality is possible because the problem has been addressed

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Document Details

Document Type
Technical Report
Publication Date
May 02, 1994
Accession Number
ADA282853

Entities

People

  • Alonzo Kelly

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Control Systems
  • Coordinate Systems
  • Dead Reckoning
  • Differential Equations
  • Geometry
  • Inertial Navigation
  • Inertial Navigation Systems
  • Kalman Filters
  • Linear Systems
  • Mathematical Filters
  • Measurement
  • Navigation
  • Probability Distributions
  • Random Variables
  • Surveys
  • Two Dimensional
  • World Geodetic System

Readers

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

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space
  • Space - Spacecraft Maneuvers