Max Robotics — Global Service Robot Directory + US Certification

About

Manuel Iori is a researcher whose work spans two distinct yet complementary domains: combinatorial optimization applied to logistics and machine learning-driven industrial automation. He has made particularly notable contributions to the field of pallet building problems, developing mathematical models, heuristic algorithms, and metaheuristic approaches — including a Reactive GRASP-based algorithm — to address complex real-world loading challenges involving constraints such as visibility, contiguity, rotation, and stackability. This body of work, inspired by real robotized industrial systems, bridges theoretical operations research with practical engineering applications. More recently, Iori has extended his expertise into industrial robotics, investigating machine learning techniques for online motion accuracy compensation in servomechanisms, targeting high-precision control in automated production environments. His 2024 contribution in this area has already attracted 12 citations, matching the impact of his earlier optimization work and signaling growing recognition across multiple research communities. With a portfolio of consistently cited publications and a clear focus on solving industrially motivated problems, Iori represents a versatile researcher whose work is valued by practitioners and academics alike seeking rigorous, applicable solutions to modern automation and logistics challenges.