Valerio Mariani

Papers

Total Citations

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About

Valerio Mariani is a researcher advancing the intersection of deep learning and autonomous navigation. His primary research areas include mobile robotics, path planning, and the integration of neural networks with classical algorithms. Mariani’s most notable contribution is his work on "Deep Learning Based Path-Planning Using CRNN and A* for Mobile Robots" (2023), which has garnered 4 citations. In this study, he pioneered a hybrid approach that combines Convolutional Recurrent Neural Networks (CRNN) with the A* search algorithm, enabling mobile robots to dynamically plan efficient, collision-free paths in complex environments. This work demonstrates his ability to merge data-driven learning with established optimization techniques, offering a scalable solution for real-time robotic navigation. While his citation count is still growing, Mariani’s research holds promise for applications in autonomous vehicles, warehouse logistics, and service robotics. His focus on practical, implementable systems underscores his commitment to bridging the gap between theoretical AI and real-world robotics challenges, making him a rising voice in the field of intelligent autonomous systems.