Fabio Allevi

Papers

Total Citations

101

H-Index

About

Fabio Allevi is a leading researcher in the field of robotics, with a primary focus on advanced control strategies for redundant manipulators and teleoperation systems. His major contributions lie in the development of robust, high-performance controllers that combine the strengths of sliding mode control (SMC) and model predictive control (MPC). His most cited work, "Operational Space Model Predictive Sliding Mode Control for Redundant Manipulators" (2020, 99 citations), introduces a novel centralized controller that leverages SMC's robustness against disturbances and MPC's predictive capabilities to achieve precise impedance control and reference tracking. This work is highly influential in the robotics community, providing a practical solution for complex manipulation tasks. Allevi has also advanced teleoperation technology with his research on robust impedance shaping for systems with time-delay, using integral sliding mode control to reject uncertainties and maintain system stability. His work is essential for improving the safety and reliability of robots in human-centric environments, from industrial automation to remote surgery.