Resumo

SEHUVERET HERNANDEZ, Dizahab; GARCIA MUNOZ, Jorge A.  e  BARRANCO GUTIERREZ, Alejandro I.. Evaluation of Metaheuristic Strategies in Robot Path Planning. EAC [online]. 2024, vol.45, n.1, pp. 27-37.  Epub 20-Maio-2024. ISSN 1815-5928.

Autonomous Ground Vehicles play a vital role in various industries, necessitating efficient route planning for mission success without human intervention. This study examines two metaheuristic optimization approaches, Genetic Algorithms and Ant Colony Optimization, within the context of route planning for these robotic entities. The comprehensive methodology utilizes the designs of these metaheuristic methods, and a comparative analysis is conducted through simulated experiments in diverse environments. The findings unveil that Genetic Algorithms excel in simple terrains; while Ant Colony Optimization demonstrates robust exploration capabilities in complex environments with obstacles and additional constraints. This underscores the importance of selecting the appropriate metaheuristic based on specific mission requirements and environmental conditions. The research furnishes insights to designers and operators, enabling informed decisions in route planning strategy selection, thereby enhancing the efficiency and safety of autonomous robotic operations across various scenarios.

Palavras-chave : Ant colony optimization; Autonomous ground vehicles; Genetic algorithms; Metaheuristic; Movil robots; Path planning.

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