An Evaluation of Image-Based Robot Orientation Estimation

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8069)


This paper describes a novel image-based method for robot orientation estimation based on a single omnidirectional camera. The estimation of orientation is computed by finding the best pixel-wise match between images as a function of the rotation of the second image. This is done either using the first image as the reference image or with a moving reference image. Three datasets were collected in different scenarios along a “Gummy Bear” path in outdoor environments. This carefully designed path has the appearance of a gummy bear in profile, and provides many curves and sets of image pairs that are challenging for visual robot localisation. We compare our method to a feature-based method using SIFT and another appearance-based visual compass. Experimental results demonstrate that the appearance-based methods perform well and more consistently than the feature based method, especially when the compared images were grabbed at positions far apart.


Robot orientation Quadtree SIFT Visual compass 


  1. 1.
    Cao, J., Labrosse, F., Dee, H.: A novel image similarity measure for place recognition in visual robotic navigation. In: Herrmann, G., Studley, M., Pearson, M., Conn, A., Melhuish, C., Witkowski, M., Kim, J.-H., Vadakkepat, P. (eds.) TAROS-FIRA 2012. LNCS, vol. 7429. Springer, Heidelberg (2012)Google Scholar
  2. 2.
    Fernández, L., Payá, L., Reinoso, Ó., Amorós, F.: Appearance-based visual odometry with omnidirectional images - a practical application to topological mapping. In: Proceedings of ICINCO, vol. 2, pp. 205–210 (2011)Google Scholar
  3. 3.
    García, D.V., Rojo, L.F., Aparicio, A.G., Castelló, L.P., García, O.R.: Visual odometry through appearance- and feature-based method with omnidirectional images. J. Robot. 2012, 1–13 (2012)CrossRefGoogle Scholar
  4. 4.
    Goecke, R., Asthana, A., Pettersson, N., Petersson, L.: Visual vehicle egomotion estimation using the Fourier-Mellin transform. In: IEEE Intelligent Vehicles Symposium, pp. 450–455 (2007)Google Scholar
  5. 5.
    Labrosse, F.: The visual compass: performance and limitations of an appearance-based method. J. Field Robot. 23(10), 913–941 (2006)CrossRefGoogle Scholar
  6. 6.
    Lourenco, M., Barreto, J.P., Vasconcelos, F.: sRD-SIFT: keypoint detection and matching in images with radial distortion. IEEE Trans. Robot. 28(3), 752–760 (2012)CrossRefGoogle Scholar
  7. 7.
    Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRefGoogle Scholar
  8. 8.
    Matthies, L., Shafer, S.: Error modeling in stereo navigation. IEEE J. Robot. Autom. 3(3), 239–250 (1987)CrossRefGoogle Scholar
  9. 9.
    Milford, M.J., Wyeth, G.F.: Single camera vision-only slam on a suburban road network. In: Proceedings of ICRA, pp. 3684–3689 (2008)Google Scholar
  10. 10.
    Moravec, H.: Obstacle avoidance and navigation in the real world by a seeing robot rover. Technical report CMU-RI-TR-80-03, Robotics Institute, Carnegie Mellon University (1980)Google Scholar
  11. 11.
    Nistr, D., Naroditsky, O., Bergen, J.: Visual odometry for ground vehicle applications. J. Field Robot. 23(1), 3–20 (2006)CrossRefGoogle Scholar
  12. 12.
    Olson, C.F., Matthies, L.H., Schoppers, M., Maimone, M.W.: Rover navigation using stereo ego-motion. Robot. Auton. Syst. 43(4), 215–229 (2003)CrossRefGoogle Scholar
  13. 13.
    Scaramuzza, D., Fraundorfer, F.: Visual odometry [tutorial]. Robot. Autom. Mag. 18(4), 80–92 (2011)CrossRefGoogle Scholar
  14. 14.
    Tomasi, C., Shi, J.: Direction of heading from image deformations. In: Proceedings of CVPR, pp. 422–427 (1993)Google Scholar
  15. 15.
    Woodland, A., Labrosse, F.: On the separation of luminance from colour in images. In: Proceedings of VVG, pp. 29–36 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceAberystwyth UniversityAberystwythUK

Personalised recommendations