Marcos Laureano

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About

Marcos Laureano is a researcher in robotics and computational intelligence, with a particular focus on the application of swarm optimization algorithms to autonomous systems. His work bridges the gap between theoretical metaheuristics and practical robotic control, most notably demonstrated in his highly cited 2019 study, "Analysis of the PSO Parameters for a Robots Positioning System in SSL." This paper systematically investigates how particle swarm optimization parameters influence the positioning accuracy of robots in the Small Size League (SSL) of RoboCup, providing critical insights for tuning autonomous navigation in dynamic environments. Though his citation count is still growing, his contribution is significant for its methodological rigor in optimizing real-time robot localization—a foundational challenge in multi-agent robotics. Laureano’s research is particularly valuable for students and engineers working on swarm robotics, sensor fusion, and adaptive control systems, offering a clear framework for improving robot performance through parameter analysis. His work exemplifies how careful empirical study of optimization algorithms can directly enhance the reliability of autonomous systems in competitive, high-speed settings.