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An Evolutionary Learning Approach for Robot Path Planning with Fuzzy Obstacle Detection and Avoidance in a Multi-agent Environment

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3 Author(s)
Cabreira, T.M. ; Programa de Pos-Grad. em Modelagem Computacional, Univ. Fed. do Rio Grande (FURG), Rio Grande, Brazil ; Dimuro, G.P. ; de Aguiar, M.S.

This paper describes a Fuzzy-Genetic Algorithm Approach for path planning of mobile robots with obstacle detection and avoidance in static and dynamic scenarios. Through the software Net logo, used in simulations of multiagent applications, a seminal model was developed for the given problem. The model, which contains a robot and scenarios with or without obstacles, is responsible for determining the best path used by a robot to achieve the goal state in a shorter number of steps and avoiding collisions. Additionally, a performance evaluation of this model in comparison with A* algorithm is presented.

Published in:

Social Simulation (BWSS), 2012 Third Brazilian Workshop on

Date of Conference:

20-23 Oct. 2012