@inproceedings{c54a315258da437a9a139128a68cc080,
title = "Evolving ant colony system for optimizing path planning in mobile robots",
abstract = "Path Planning is one of the problems in robotics. It consists on automatically determine a path from an initial position of the robot to its final position. In this paper we propose a variant of the ant colony system (ACO) applied to optimize the path that a robot can follow to reach its target destination. We also propose to evolve some parameters of the ACO algorithm by using a genetic algorithm (ACO-GA) to optimize the search of the shortest path. We compare the accuracy of ACO against ACO-GA using real environments.",
author = "Garro, {Beatriz A.} and Humberto Sossa and V{\'a}zquez, {Roberto A.}",
year = "2007",
doi = "10.1109/CERMA.2007.4367727",
language = "Ingl{\'e}s",
isbn = "0769529747",
series = "Electronics, Robotics and Automotive Mechanics Conference, CERMA 2007 - Proceedings",
pages = "444--449",
booktitle = "Electr., Rob. Autom. Mech. Conf., CERMA - Proc.",
note = "Electronics, Robotics and Automotive Mechanics Conference, CERMA 2007 ; Conference date: 25-09-2007 Through 28-09-2007",
}