A primary goal for an autonomous mobile robot is to explore and perfrom simultaneous localization and mapping (SLAM). During SLAM, the robot must balance the opposing desires of pose certainty maintenance and information gain. Much of previous research has ignored the need of pose maintenance. This paper provides the first step in developing a neural dynamics based algorithm which considers both information gain and pose maintenance when determining the robot's next pose. Simulation results show that the algorithm is able to provide the robot with an exploration plan to fully explore the tested environments. The next step is to apply the algorithm in a full SLAM environment. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Bueckert, J., & Yang, S. X. (2007). Neural dynamics based exploration algorithm for a mobile robot. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4669 LNCS, pp. 640–649). Springer Verlag. https://doi.org/10.1007/978-3-540-74695-9_66
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