Maria Vittoria Minniti
Papers
6
Total Citations
297
H-Index
6
About
Maria Vittoria Minniti is a leading roboticist whose research lies at the intersection of whole-body control, model predictive control (MPC), and autonomous mobile manipulation. Her work focuses on enabling dynamically stable robots—particularly legged manipulators and quadrupedal platforms—to perform complex, real-world tasks that require both mobility and dexterity. Her most cited paper, “Whole-Body MPC for a Dynamically Stable Mobile Manipulator” (101 citations), introduces a unified optimization framework that jointly solves manipulation, balancing, and interaction problems. She further advanced the field with “Adaptive CLF-MPC With Application to Quadrupedal Robots” (71 citations), which combines control Lyapunov functions with MPC for robust locomotion and payload handling. Minniti has also pioneered Bayesian multi-task learning for MPC (45 citations) to enable robots to adapt to diverse tasks like door opening and pick-and-place. Her work on collision detection and identification for legged manipulators (16 citations) and passivity-based control for haptic teleoperation (15 citations) underscores her commitment to safe, reliable human-robot interaction. A researcher at the intersection of theory and application, Minniti’s contributions are shaping the next generation of autonomous, contact-rich robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Whole-Body MPC for a Dynamically Stable Mobile Manipulator101 citations · 2019
- 2Adaptive CLF-MPC With Application to Quadrupedal Robots71 citations · 2021
- 3
- 4Bayesian Multi-Task Learning MPC for Robotic Mobile Manipulation45 citations · 2023
- 5Collision detection and identification for a legged manipulator16 citations · 2022
- 6