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Estimation, Search, and Planning (ESP) Research Group

Rover odometry aided by a star tracker

  1. Jonathan D. Gammell
  2. Chi Hay Tong
  3. Peter Berczi
  4. Sean Anderson
  5. Timothy D. Barfoot
  6. John Enright
Publication Date

This paper develops a practical framework for estimating rover position in full-dark conditions by correcting relative odometric estimates with periodic, absolute-attitude measurements from a star tracker. The framework is validated using just under 2.5 kilometres of field data gathered at the University of Toronto’s Koffler Scientific Reserve at Jokers Hill (KSR) comprised of both wheel odometry and lidar-based Visual Odometry (VO). It is shown that for the wheel odometry solution, the final estimate of rover position was within 21 metres of the groundtruth as calculated by a differential GPS receiver, or 0.85% of the total traverse distance. When the star tracker measurements are artificially limited to occurring approximately every 250 metres, the algorithm still performs well, giving a final position error of 75.8 metres or 3.0%. Preliminary results to replace wheel odometry with lidar-based VO for the development a full-dark visual solution are also presented. The lidar-based VO solution is shown to be capable of outperforming wheel odometry, but more work is required to develop methods to handle the variety of terrain conditions encountered.

Publication Details
Full-Paper-Refereed Conference Paper
IEEE Aerospace Conference
Big Sky, MT, USA
Digital Object IdentifierDOI
Open-Access PDF (Recommended)PDF
https://robotic-esp.com/papers/gammell_ieeeac13.pdf (corrected version)
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BibTeX Entry
author = {Jonathan D Gammell and Chi Hay Tong and Peter Berczi and Sean Anderson and Timothy D Barfoot and John Enright},
title = {Rover odometry aided by a star tracker},
booktitle = {Proceedings of the {IEEE} Aerospace Conference},
year = {2013},
pages = {1--10},
address = {Big Sky, MT, USA},
month = {2--9 } # mar,
doi = {10.1109/AERO.2013.6496953},