Occupancy Grid-Based SLAM Using a Mobile Robot with a Ring of Eight Sonar Transducers

  • George Terzakis
  • Sanja Dogramadzi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6856)


The degree of accuracy by which a mobile robot can estimate the properties of its surrounding environment, and the ability to successfully navigate throughout the explored space are the main factors that may well determine its autonomy and efficiency with respect to the goals of the application. This paper focuses on the implementation of a SLAM framework comprising a planner, a percept and a displacement/angular error estimator using a regular occupancy grid spatial memory representation.


Mobile Robot Finite State Machine Markov Random Field Occupancy Grid Motion Primitive 
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.


  1. 1.
    Murphy, R.: Introduction to AI Robotics, pp. 42–44. MIT Press, Cambridge (2001)Google Scholar
  2. 2.
    Elfes, A.: Using occupancy grids for mobile robot perception and navigation. Carnegie Mellon University, Pittsburgh (1989)Google Scholar
  3. 3.
    Theodoridis, S., Koutroumbas, S.: Pattern Recognition, 4th edn., pp. 14–16. Elsevier Inc., San Diego (2009)zbMATHGoogle Scholar
  4. 4.
    Welch, G., Bishop, G.: An introduction to the Kalman filter. University of North Carolina, Chapel Hill (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • George Terzakis
    • 1
  • Sanja Dogramadzi
    • 2
  1. 1.School of Computing and MathematicsUniversity of PlymouthPlymouthUK
  2. 2.Department of Engineering Design and MathematicsUniversity of the West of EnglandBristolUK

Personalised recommendations