Giulio Romualdi
Papers
19
Total Citations
241
H-Index
8
About
Giulio Romualdi is a robotics researcher specializing in humanoid robot locomotion, motion planning, and whole-body control, with a particular focus on advancing the capabilities of legged robotic systems. His most influential contribution, the iCub3 avatar system (2024, 60 citations), demonstrates his ability to bridge cutting-edge hardware and human-robot interaction, enabling immersive teleoperation of humanoid platforms developed at the Istituto Italiano di Tecnologia. Romualdi has made significant strides in model predictive control for bipedal locomotion, most notably through his nonlinear centroidal MPC framework (2022, 50 citations), which enables real-time step adjustment and robust dynamic walking. His trajectory optimization work, incorporating complementarity conditions and full centroidal kinematics, further establishes him as a leading voice in principled motion generation for humanoids. Romualdi has also explored machine learning integration through the ADHERENT framework, which brings human-like movement qualities to robotic locomotion, and has tackled practical sensing challenges via physics-informed neural networks and Kalman filtering for sensorless torque estimation. Across more than ten peer-reviewed contributions accumulating nearly 215 citations, his work consistently pushes the boundary between theoretical rigor and deployable robotic systems.
Research Focus
Key Achievements
Top Papers
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- 7Modeling of Visco-Elastic Environments for Humanoid Robot Motion Control9 citations · 2021
- 8Whole-Body Trajectory Optimization for Robot Multimodal Locomotion9 citations · 2022
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- 10UKF-Based Sensor Fusion for Joint-Torque Sensorless Humanoid Robots5 citations · 2024