Abstract
We present here a neural model for mobile robot action selection and trajectories planning. It is based on the elaboration of a “cognitive map”. This cognitive map builds up a graph linking together reachable places. We first demonstrate that this map may be used for the control of the robot speed assuring a convergence to the goal. We show afterwards that this model enables to select between different goals in a static environment and finally in a changing environment.
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Quoy, M., Gaussier, P., Leprêtre, S., Revel, A., Banquet, JP. (2000). A Planning Map for Mobile Robots: Speed Control and Paths Finding in a Changing Environment. In: Wyatt, J., Demiris, J. (eds) Advances in Robot Learning. EWLR 1999. Lecture Notes in Computer Science(), vol 1812. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40044-3_7
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DOI: https://doi.org/10.1007/3-540-40044-3_7
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