Luigi Glielmo

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About

Luigi Glielmo is a prominent figure in control systems engineering and robotics, with a research focus that bridges theoretical foundations and practical applications. His work primarily explores intelligent control, path-planning, and optimization for autonomous systems, particularly mobile robots. A notable contribution is his 2023 paper "Deep Learning Based Path-Planning Using CRNN and A* for Mobile Robots," which integrates convolutional recurrent neural networks with classical A* algorithms to enhance real-time navigation efficiency. While this specific work has garnered 4 citations, Glielmo’s broader impact is reflected in his extensive publication record on model predictive control, nonlinear systems, and energy management—areas where his papers have collectively accumulated hundreds of citations. His research has advanced adaptive control strategies for complex environments, influencing fields from automotive systems to industrial automation. Glielmo’s achievements include leadership roles in major European research projects and editorial positions in top-tier journals, underscoring his reputation as a rigorous scholar dedicated to bridging algorithmic innovation with real-world robotics challenges.