Horus: Object Orientation and Id without Additional Markers

  • Jacky Baltes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1998)


This paper describes a novel approach to detecting orientation and identity of robots using a global vision system. Instead of additional markers, the original shape of the robot is used to determine an orientation using a general Hough transform. In addition the movement history as well as the command history are used to calculate the quadrant of the orientation as well as the identity of the robot. An empirical evaluation shows that the performance of the new video server is at least as good as that of a traditional approach using additional colored markers.


Additional Marker Orientation Information Edge Pixel Video Server Object Orientation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    D. H. Ballard: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (1981) 111–122. 111zbMATHCrossRefGoogle Scholar
  2. 2.
    J. Baltes, Y. Lin: Path-tracking control of non-holonomic car-like robots using reinforcement learning. In: Proceed. of the IJCAI Workshop on RoboCup, Stockholm, Sweden, (July 1999). 114Google Scholar
  3. 3.
    M. Egerstedt, X. Hu, A Stotsky: Control of a car-like robot using a dynamic model. In: IEEE-Proceed. of the Conf. on Robotics and Automation, Leuven, Belgium, (1998). 114Google Scholar
  4. 4.
    R. Y. Tsai: An efficient and accurate camera calibration technique for 3d machine vision. In: IEEE-Proceed. of Conf. on Computer Vision and Pattern Recognition, Miami Beach, FL, (1986) 364–374. 108Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Jacky Baltes
    • 1
  1. 1.Center for Image Technology and RoboticsUniversity of AucklandAucklandNew Zealand

Personalised recommendations