Advertisement

Enhancing the Reactivity of the Vision Subsystem in Autonomous Mobile Robots Using Real-Time Techniques

  • Paulo Pedreiras
  • Filipe Teixeira
  • Nelson Ferreira
  • Luís Almeida
  • Armando Pinho
  • Frederico Santos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4020)

Abstract

Interest on using mobile autonomous agents has been growing, recently, due to their capacity to cooperate for diverse purposes, from rescue to demining and security. In many of these applications the environments are inherently unstructured and dynamic, requiring substantial computation resources for gathering enough sensory input data to allow a safe navigation and interaction with the environment. As with humans, who depend heavily on vision for these purposes, mobile robots employ vision frequently as the primary source of input data when operating in such environments. However, vision-based algorithms are seldom developed with reactive and real-time concerns, exhibiting large variations in the execution time and leading to occasional periods of black-out or vacant input data. This paper addresses this problem in the scope of the CAMBADA robotic soccer team developed at the University of Aveiro, Portugal. It presents an evolution from a monolithic to a modular architecture for the vision system that improves its reactivity. With the proposed architecture it is possible to track different objects with different rates without losing any frames.

Keywords

Controller Area Network Modular Architecture Obstacle Detection Autonomous Mobile Robot Robotic Agent 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Controller Area Network - CAN2.0 (1992). Technical Specification, Robert Bosch (1992)Google Scholar
  2. 2.
    Gibson, J.: The Ecological Approach to Visual Perception. Houghton Mifflin, Boston (1979)Google Scholar
  3. 3.
    Santos, F., Almeida, L., Pedreiras, P., Lopes, L.S., Facchinnetti, T.: An Adaptive TDMA Protocol for Soft Real-Time Wireless Communication Among Mobile Computing Agents. In: WACERTS 2004, Workshop on Architectures for Cooperative Embedded Real-Time Systems (satellite of RTSS 2004), Lisboa, Portugal, December 5-8 (2004)Google Scholar
  4. 4.
    DeSouza, G.N., Kak, A.C.: A Subsumptive, Hierarchical, and Distributed Vision-Based Architecture for Smart Robotics. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 34, 1988–2002 (2004)CrossRefGoogle Scholar
  5. 5.
    RTAI for Linux, available at: http://www.aero.polimi.it/~rtai/
  6. 6.
    Almeida, L., Santos, F., Facchinetti, T., Pedreiras, P., Silva, V., Lopes, L.S.: Coordinating distributed autonomous agents with a real-time database: The CAMBADA project. In: Aykanat, C., Dayar, T., Körpeoğlu, İ. (eds.) ISCIS 2004. LNCS, vol. 3280, pp. 876–886. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Kitano, K., Asada, M., Kuniyoshi, Y., Noda, I., Osawa, E.: RoboCup: The Robot World Cup Initiative. In: Proc. of IJCAI 1995 Workshop on Entertainment and AI/Alife, Montreal (1995)Google Scholar
  8. 8.
    Kopetz, H.: Real-Time Systems Design Principles for Distributed Embedded Applications. Kluwer Academic Publishers, Dordrecht (1997)MATHGoogle Scholar
  9. 9.
    Proc. of the NASA Workshop on Biomorphic Robotics, Jet Propulsion Laboratory, California Institute of Technology,USA (2000)Google Scholar
  10. 10.
    Iannizzotto, G., La Rosa, F., Lo Bello, L.: Real-time issues in vision-based Human-Computer Interaction. Technical Report, VisiLab, University of Messina, Italy (2004)Google Scholar
  11. 11.
    Weiss, G.: Multiagent systems. A Modern Approach to Distributed Artificial Intelligence. MIT Press, Cambridge (2000)Google Scholar
  12. 12.
    Simple DirectMedia Layer, available at: http://www.libsdl.org/index.php
  13. 13.
    Blake, A., Curwen, R., Zisserman, A.: A framework for spatio-temporal control in the tracking of visual contours. Int. Journal of Computer Vision 11(2), 127–145 (1993)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Paulo Pedreiras
    • 1
  • Filipe Teixeira
    • 2
  • Nelson Ferreira
    • 2
  • Luís Almeida
    • 1
  • Armando Pinho
    • 1
  • Frederico Santos
    • 3
  1. 1.LSE-IEETA/DETUniversidade de Aveiro AveiroPortugal
  2. 2.DETUniversidade de Aveiro AveiroPortugal
  3. 3.DEEInstituto Politécnico de CoimbraCoimbraPortugal

Personalised recommendations