Abstract
In this paper, we study the path planning for Khepera II mobile robot in a grid map environment using an extended Q-learning algorithm. The extension offers an additional benefit of avoiding unnecessary computations involved to update the Q-table. A flag variable is used to keep track of the necessary updating in the entries of the Q-table. The validation of the algorithm is studied through real time execution on Khepera-II platform. An analysis reveals that there is a significant saving in time- and space- complexity of the proposed algorithm with respect to classical Q-learning. © 2010 Springer-Verlag.
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CITATION STYLE
Goswami, I., Das, P. K., Konar, A., & Janarthanan, R. (2010). Extended Q-learning algorithm for path-planning of a mobile robot. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6457 LNCS, pp. 379–383). https://doi.org/10.1007/978-3-642-17298-4_40
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