Abstract
Mobile robots often operate in domains that are incompletely known. This article addresses the goal-directed navigation problem in unknown terrain where a mobile robot has to move from its current configuration to given goal configuration. We will present tests performed with various implementations of graph search algorithms (A*, D*, focused D*) as path planners for a mobile robot, focusing on the inherent strong points and drawbacks of each implementation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Berg, J.V.D.: Anytime path planning and replanning in dynamic environments. In: Proceedings of the International Conference on Robotics and Automation, pp. 2366–2371 (2006)
Eklund, P.W., Kirkby, S., Pollitt, S.: A dynamic multi-source Dijkstra’ algorithm for vehicle routing. In: Proc. of Conf. on Intelligent Information Systems, Australia and New Zealand (1996)
LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006)
Bonet, B., Geffner, H.: Planning as heuristic search. Artificial Intelligence 129, 5–33 (2004)
Goldberg, A.V., Harrelson, C.: Computing the shortest path: A* search meets graph theory. In: Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 156–165 (2005)
Brumitt, B., Stentz, A.: GRAMMPS: a generalized mission planner for multiple mobile robots. In: Proceedings of the International Conference on Robotics and Automation (1998)
Koenig, S., Likhachev, M.: Incremental A*. In: Advances in Neural Information Processing Systems, vol. 14. MIT Press (2002)
Buckland, M.: AI techniques for game programming. Premier Press, Portland (1992)
Hansen, E.A., Zhou, R.: Anytime heuristic search. Journal of Artificial Intelligence Research (JAIR) 28, 267–297 (2007)
Stentz, A.: The focussed D* algorithm for real-time replanning. International Journal of Robotics and Automation (1995)
Stentz, A.: Optimal and efficient path planning for partially-known environments. In: Proceedings IEEE International Conference on Robotics & Automation, pp. 3310–3317 (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Robotin, R., Lazea, G., Dobra, P. (2013). Mobile Robot Navigation Using Graph Search Techniques over an Approximate Cell Decomposition of the Free Space. In: Dumitrache, L. (eds) Advances in Intelligent Control Systems and Computer Science. Advances in Intelligent Systems and Computing, vol 187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32548-9_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-32548-9_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32547-2
Online ISBN: 978-3-642-32548-9
eBook Packages: EngineeringEngineering (R0)