Correction of inertial navigation system's errors by the help of video-based navigator based on Digital Terrarium Map

TL;DR

This paper presents a novel video-based navigation algorithm that uses optical flow and digital terrain maps to estimate a moving camera's position and orientation without explicit 3D reconstruction, with validated accuracy through simulations.

Contribution

It introduces an error analysis and closed-form uncertainty expression for a terrain-based navigation method that does not require 3D world reconstruction.

Findings

The algorithm accurately estimates pose under reasonable error conditions.

Optical flow evaluation and terrain data quality are key error sources.

Simulations confirm the robustness of the proposed method.

Abstract

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.