Abstract
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Murphy, R.: Introduction to AI Robotics, pp. 42–44. MIT Press, Cambridge (2001)
Elfes, A.: Using occupancy grids for mobile robot perception and navigation. Carnegie Mellon University, Pittsburgh (1989)
Theodoridis, S., Koutroumbas, S.: Pattern Recognition, 4th edn., pp. 14–16. Elsevier Inc., San Diego (2009)
Welch, G., Bishop, G.: An introduction to the Kalman filter. University of North Carolina, Chapel Hill (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Terzakis, G., Dogramadzi, S. (2011). Occupancy Grid-Based SLAM Using a Mobile Robot with a Ring of Eight Sonar Transducers. In: Groß, R., Alboul, L., Melhuish, C., Witkowski, M., Prescott, T.J., Penders, J. (eds) Towards Autonomous Robotic Systems. TAROS 2011. Lecture Notes in Computer Science(), vol 6856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23232-9_48
Download citation
DOI: https://doi.org/10.1007/978-3-642-23232-9_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23231-2
Online ISBN: 978-3-642-23232-9
eBook Packages: Computer ScienceComputer Science (R0)