Leonardo Maretto

Papers

Total Citations

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About

Leonardo Maretto is a researcher focused on advancing human-robot collaboration, particularly in industrial and manufacturing contexts. His work centers on making collaborative robots (cobots) safer and more efficient in shared workspaces. Maretto’s most-cited paper, “The influence of collision avoidance strategies on human-robot collaborative systems” (2022, 8 citations), tackles a core challenge: the shared workspace is both the greatest asset and the greatest limitation of cobots. He analyzes how different collision avoidance algorithms affect system performance and operator trust, providing critical insights for designing safer, more fluid interactions. In his subsequent work, “Dynamic Task Allocation for Collaborative Robot Systems” (2023, 3 citations), Maretto explores how tasks can be intelligently distributed between humans and robots in real time, optimizing productivity without compromising safety. His contributions are particularly valuable for industries transitioning to flexible, human-centric automation. By addressing the tension between efficiency and safety, Maretto is helping shape the next generation of collaborative manufacturing environments where humans and robots work side by side seamlessly.