Abstract
A multiagent system to support a mobile robot motion planning has been presented. Baptized MARCoPlan (MutiAgent Remote Control motion Planning), this system deals with optimizing robot path. Considered as an agent, the robot has to optimize its motion from a start position to a final goal in a dynamic and unknown environment, on the one hand by the introduction of sub-goals, and on the other hand by the cooperation of multiagents. In fact, we propose to agentify the proximity environment (zones) of the robot; cooperation between theses zones agents will allow the selection of the best sub-goal to be reached. Therefore, the task of the planner agent to guide the robot to its destination in an optimized way will be easier. MARCoPlan is simulated and tested using randomly and dynamically generated problem instances with different distributions of obstacles. The tests verify some robustness of MARCoPlan with regard to environment changes. Moreover, the results highlight that the agentification and the cooperation improve the choice of the best path to the sub goals, then to the final goal.
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Kefi, S., Barhoumi, I., Kallel, I., Alimi, A.M. (2008). MARCoPlan: MultiAgent Remote Control for Robot Motion Planning. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_77
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DOI: https://doi.org/10.1007/978-3-540-69731-2_77
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