Matteo Poggiali

Papers

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About

Matteo Poggiali is a leading researcher in human-robot collaboration and manufacturing logistics, with a focus on optimizing kitting processes—the assembly of grouped items for production lines. His most-cited work, "An online scheduling algorithm for human-robot collaborative kitting" (2020, 17 citations), addresses a critical challenge in modern factories: reducing the physical strain on human operators who perform repetitive arm motions in warehouse picking. Poggiali’s key contribution lies in developing adaptive scheduling algorithms that enable robots and humans to work side-by-side efficiently, dynamically allocating tasks to minimize worker fatigue while maintaining throughput. This research bridges industrial engineering and robotics, offering practical solutions for safer, more productive assembly lines. Beyond this flagship paper, his work has influenced the design of collaborative systems that prioritize human well-being without sacrificing operational speed. With growing citation impact, Poggiali is recognized for advancing the integration of intelligent automation in logistics, making him a pivotal figure in the evolution of Industry 5.0—where human-centricity meets technological innovation.