Andrea Tomasi
Papers
1
Total Citations
3
H-Index
1
About
Andrea Tomasi is a researcher whose work lies at the intersection of collaborative robotics and physical human-robot interaction (pHRI), with a particular focus on making robots more intuitive and responsive to human partners. Her key research areas include human motion intention estimation, variable admittance control, and the development of adaptive robotic systems for manual guidance tasks. In her most cited work, "Human intention estimation and goal-driven variable admittance control in manual guidance applications" (2021), Tomasi tackles the critical challenge of predicting a human operator’s intended target during physical collaboration. By integrating intention estimation with a goal-driven variable admittance controller, she enables robots to dynamically adjust their compliance and assistance, significantly improving the fluidity and effectiveness of human-robot teamwork. This contribution is foundational for applications in manufacturing, rehabilitation, and assistive technologies. With 3 citations to date, her work is gaining traction as a practical solution for enhancing synergy in shared tasks. Tomasi’s research stands out for its focus on real-time adaptability, bridging the gap between human cognitive intent and robotic action—a vital step toward truly collaborative automation.
Research Focus
Key Achievements
Top Papers
- 1