Max Robotics — Global Service Robot Directory + US Certification

About

Samuele Sandrini is a leading researcher in human-robot collaboration, focusing on making industrial robotics safer, more efficient, and truly synergistic. His work centers on three key areas: task planning and scheduling for heterogeneous agents, learning-based coordination, and safety in dynamic environments. Sandrini’s major contributions include developing human-aware task allocation models that optimize synergy between human operators and robots, and pioneering methods to learn action durations and interdependencies—crucial for seamless collaboration. His 2025 paper on “Learning and planning for optimal synergistic human–robot coordination” (11 citations) and his 2022 work on “Learning Action Duration and Synergy in Task Planning” (11 citations) are foundational, proposing novel mixed-integer programming and learning frameworks. He has also advanced safety protocols, such as reference frame procedures for safe interaction (2023, 4 citations), and human motion prediction using Unscented Kalman Filters (2024, 3 citations) to enhance both safety and efficiency. Sandrini’s research directly addresses real-world manufacturing challenges, bridging the gap between theoretical planning and practical, adaptive coordination. His work is essential reading for anyone interested in the future of collaborative robotics and intelligent manufacturing systems.