Real-Time Localization for Mobile Machines by Fusing Barometric Altitude Measurements with Surface Profiles

EasyChair Preprint 8343

Abstract

Accurate localization is one of the key requirements for the automation of mobile machines. While GNSS-based systems are widely used due to their high accuracy and accessibility, redundant systems have to be developed to decrease the dependency on GNSS signals for autonomous machines. Although altitude measurements have been used for many decades by human explorers, they are not yet exploited for localization purposes on mobile machines. Based on single barometric measurements, no localization is possible as the vehicle could be at various positions with the same absolute altitude. In this paper, we propose an algorithm based on sequential importance sampling to fuse altitude measurements with surface profiles, which allows real-time tracking and localization of mobile machines. When moving through hilly terrain, a machine constantly changes its altitude, and the altitude profile can be used to track the vehicle's position. The proposed algorithm offers a supplementary localization and verification method for mountainous and potentially GNSS-obstructed areas.

Keyphrases: Localization, Robotics, Tracking, autonomous systems, mobile machines

@booklet{EasyChair:8343,
  author    = {Lukas Michiels and Benjamin Kazenwadel and Simon Becker and Marcus Geimer},
  title     = {Real-Time Localization for Mobile Machines by Fusing Barometric Altitude Measurements with Surface Profiles},
  howpublished = {EasyChair Preprint 8343},
  year      = {EasyChair, 2022}}