Abstract
This paper presents a robot solution that allows to automatically reach a set of goals attributed to a robot. The challenge is to design autonomous robots assigned to perform missions without a predefined plan. We address the stochastic salesman problem where the goal is to visit a set of points of interest. A stochastic Road-Map is defined as a topological representation of an unstructured environment with uncertainty on the path achievement. The Road-Map allows us to split deliberation and reactive control. The proposed decision making uses a computation of Markov Decision Processes (MDPs) in order to plan all the reactive tasks to perform while there are goals not yet reached. Finally, from a brief explanation on how the approach could be extend to multi-robot missions, experiments in real conditions permit to evaluate the proposed architecture for multi-robot stochastic salesmen missions.
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Lozenguez, G., Adouane, L., Beynier, A., Mouaddib, AI., Martinet, P. (2013). Interleaving Planning and Control of Mobiles Robots in Urban Environments Using Road-Map. In: Lee, S., Cho, H., Yoon, KJ., Lee, J. (eds) Intelligent Autonomous Systems 12. Advances in Intelligent Systems and Computing, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33926-4_65
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DOI: https://doi.org/10.1007/978-3-642-33926-4_65
Publisher Name: Springer, Berlin, Heidelberg
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