3 citations · 5 across the 9 of their papers we have counts for
11 papers
A machine learning framework for uncovering stochastic nonlinear dynamics from noisy data
Matteo Bosso, Giovanni Franzese, Kushal Swamy +3
Modeling real-world systems requires accounting for noise - whether it arises from unpredictable fluctuations in financial markets, irregular rhythms in biological systems, or envi…
MUKCa: Accurate and Affordable Cobot Calibration Without External Measurement Devices
Giovanni Franzese, Max Spahn, Jens Kober +1
To increase the reliability of collaborative robots in performing daily tasks, we require them to be accurate and not only repeatable. However, having a calibrated kinematics model…
Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning
Domenico Dona', Giovanni Franzese, Cosimo Della Santina +2
Industrial robotics demands significant energy to operate, making energy-reduction methodologies increasingly important. Strategies for planning minimum-energy trajectories typical…
Mastering Contact-rich Tasks by Combining Soft and Rigid Robotics with Imitation Learning
Mariano Ramírez Montero, Ebrahim Shahabi, Giovanni Franzese +3
Soft robots have the potential to revolutionize the use of robotic systems with their capability of establishing safe, robust, and adaptable interactions with their environment, bu…
ILeSiA: Interactive Learning of Robot Situational Awareness from Camera Input
Petr Vanc, Giovanni Franzese, Jan Kristof Behrens +4
Learning from demonstration is a promising approach for teaching robots new skills. However, a central challenge in the execution of acquired skills is the ability to recognize fau…
Generalizable Motion Policies through Keypoint Parameterization and Transportation Maps
Giovanni Franzese, Ravi Prakash, Cosimo Della Santina +1
Learning from Interactive Demonstrations has revolutionized the way non-expert humans teach robots. It is enough to kinesthetically move the robot around to teach pick-and-place, d…