Experimental Results of Testing a Direct Monocular Visual Odometry Algorithm Outdoors on Flat Terrain under Severe Global Illumination Changes for Planetary Exploration Rovers

Authors

  • Geovanni Martínez Image Processing and Computar Vision Research Laboratory (IPCV-LAB) - University of Costa Rica

DOI:

https://doi.org/10.13053/cys-22-4-2839

Keywords:

Visual-based Autonomous Navigation, Planetary Rover Localization, Ego-Motion Estimation, Visual Odometry, Experimental Validation, Planetary Robots

Abstract

We present the experimental results obtained by testing a monocular visual odometry algorithm on a real robotic platform outdoors, on flat terrain, and under severe changes of global illumination. The algorithm was proposed as an alternative to the long-established feature based stereo visual odometry algorithms. The rover's 3D position is computed by integrating the frame to frame rover's 3D motion over time. The frames are taken by a single video camera rigidly attached to the rover looking to one side tilted downwards to the planet's surface. The frame to frame rover's 3D motion  is directly estimated by maximizing the likelihood function of the intensity differences at key observation points, without establishing correspondences between features or solving the optical flow as an intermediate step, just directly evaluating the frame to frame intensity differences measured at key observation points. The key observation points are image points with high linear intensity gradients. Comparing the results with the corresponding ground truth data, which was obtained by using a robotic theodolite with a laser range sensor, we concluded that the algorithm is able to deliver the rover's position in average of 0.06 seconds after an image has been captured and with an average absolute position error of 0.9% of distance traveled. These results are quite similar to those reported in scientific literature for traditional feature based stereo visual odometry algorithms, which were successfully used in real rovers here on Earth and on Mars.  We believe that they represent an important step towards the validation of the algorithm and make us think that it may be an excellent tool for any autonomous robotic platform, since it could be very helpful in situations in which the traditional feature based visual odometry algorithms have failed. It may also be an excellent candidate to be merged with other positioning algorithms and/or sensors.

Author Biography

Geovanni Martínez, Image Processing and Computar Vision Research Laboratory (IPCV-LAB) - University of Costa Rica

Geovanni Martinez  earned his PhD. (Dr.-Ing.) from the Institut fuer Theoretische Nachrichtentechnik und Informationsverarbeitung at the University of Hannover, Germany, in 1998. His PhD. thesis dealt with shape, motion and color estimation of articulated objects for video compression. His PhD advisor was Prof. H.-G. Musmann. From August 2000 to June 2002, he conducted posdoctoral research work on optical tracking for teleoperation space applications at the University of Houston and NASA - Johnson Space Center. In 1997 he joined the Faculty at the University of Costa Rica, where he is now Full Professor. He is the founder and coordinator of the Image Processing and Computer Vision Research Laboratory (IPCV-LAB). He is the recipient of the 2002 "Clodomiro Picado Twight" National Technology Award and in the year 2010 he was named Researcher of the Year in Engineering by the University of Costa Rica.

Downloads

Published

2018-12-30

Issue

Vol. 22 No. 4 (2018): Topic Trends in Computing Research (Guest Editors: A. Aguilar-Meléndez, E. Moya-Sánchez)

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.