Max Robotics — Global Service Robot Directory + US Certification

About

Luca Di Persio is a researcher at the forefront of stochastic modeling and control theory for robotic systems, with a particular focus on wheeled mobile robots and teleoperation. His work bridges the gap between probabilistic mathematics and practical robotics, introducing novel frameworks that enhance both safety and efficiency. His most-cited paper, "A Brownian–Markov stochastic model for cart-like wheeled mobile robots" (2023, 8 citations), provides a rigorous probabilistic foundation for robot motion under uncertainty. In "Bilateral teleoperation of stochastic port‐Hamiltonian systems using energy tanks" (2021, 7 citations), he developed a passivity-preserving energy tank method for stochastic systems, enabling stable bilateral teleoperation—a critical contribution to remote robotic control. More recently, his "Minimum-energy switching geometric filter on Lie groups" (2024, 3 citations) advances state estimation for differential-drive robots, while "Dynamic Movement Primitives With Control Barrier Functions" (2025) integrates imitation learning with safety constraints. With a total of 19 citations across these works, Di Persio’s research is steadily gaining recognition for its innovative synthesis of stochastic analysis, geometric control, and real-world robotic applications, making him a promising voice in modern robotics theory.