Advertisement

Visual Tracking and Localization of a Small Domestic Robot

  • Raymond Sheh
  • Geoff West
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)

Abstract

We investigate the application of a Monte Carlo localization filter to the problem of combining local and global observations of a small, off-the-shelf quadruped domestic robot, in a simulated Smart House environment, for the purpose of robust tracking and localization. A Sony Aibo ERS-210A robot forms part of this project, with the ultimate aim of providing additional monitoring, human-system interaction and companionship to the occupants.

Keywords

Ground Plane Quadruped Robot Monte Carlo Localization Overhead Camera Domestic Robot 
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.

References

  1. 1.
    Chen, J., Chung, E., Edwards, R., Mak, E., Sheh, R., Sutanto, N., Tam, T., Tang, A., Wong, N.: rUNSWift, UNSW RoboCup 2003 Sony Legged League Team. Honours thesis, School of Computer Science and Engineering, The University of New South Wales (2003)Google Scholar
  2. 2.
    Dellaert, F., Fox, D., Burgard, W., Thrun, S.: Monte carlo localization for mobile robotsGoogle Scholar
  3. 3.
    Dempster, P., Laird, N.M., Rubin, D.B.: Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society. Series B (Methodological) 39(1), 1–38 (1977)zbMATHMathSciNetGoogle Scholar
  4. 4.
    Peursum, P., Venkatesh, S., West, G.A.W., Bui, H.H.: Object labelling from human action recognition. In: IEEE Conference on Pervasive Computing and Communications, March 2003, pp. 399–406 (2003)Google Scholar
  5. 5.
    Schalkoff, R.J.: Digital Image Processing and Computer Vision. John Wiley and Sons, Chichester (1989)Google Scholar
  6. 6.
    Sheh, R., Hengst, B.: Nightowl: Self-localisation by matching edges. Technical Report UNSW-CSE-TR-0406, School of Computer Science and Engineering, University of New South Wales (2004)Google Scholar
  7. 7.
    Stauffer, C., Grimson, W.E.L.: Learning patterns of activity using realtime tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(8), 747–757 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Raymond Sheh
    • 1
  • Geoff West
    • 1
  1. 1.Department of ComputingCurtin University of TechnologyPerthAustralia

Personalised recommendations