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Exploratory Path Planning Using the Max-Min Ant System Algorithm

Santos, Valeria, Otero, Fernando E.B., Johnson, Colin G., Osorio, Fernando, Toledo, Claudio (2016) Exploratory Path Planning Using the Max-Min Ant System Algorithm. In: 2016 IEEE Congress on Evolutionary Computation (CEC 2016). . pp. 4229-4235. E-ISBN 978-1-5090-0623-6. (doi:10.1109/CEC.2016.7744327)

Abstract

In the path planning problem for autonomous mobile robots, robots have to plan their path from the start position to the goal. In this paper, we investigate the application of the MMAS algorithm to the exploratory path planning problem, in which the robots should explore the environment at the same time they plan the path. Max-min ant system is an ant colony optimization algorithm that exploits the best solutions found. In addition, to analyze the quality of solutions obtained, we also analyze the traveled distance spent by robots in the first iteration of the algorithm. The environment is previously unknown to the robots, although it is represented by a topological map, that does not require precise information from the environment and provides a simple way to execute the navigation of the path. Thus, the paths are represented by a sequence of actions that the robots should execute to reach the goal. The navigation of the best solution found was implemented in a realistic robotic simulator. The proposed algorithm provides a very good performance in relation to a genetic algorithm and the well-known A* algorithm that deal with this problem.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/CEC.2016.7744327
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Fernando Otero
Date Deposited: 22 Apr 2016 09:46 UTC
Last Modified: 01 Aug 2019 10:40 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/55108 (The current URI for this page, for reference purposes)
Otero, Fernando E.B.: https://orcid.org/0000-0003-2172-297X
Johnson, Colin G.: https://orcid.org/0000-0002-9236-6581
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