257 citations · 996 across the 51 of their papers we have counts for
5 papers · 1 filter
A Black-Box Physics-Informed Estimator based on Gaussian Process Regression for Robot Inverse Dynamics Identification
Giulio Giacomuzzos, Ruggero Carli, Diego Romeres +1
Learning the inverse dynamics of robots directly from data, adopting a black-box approach, is interesting for several real-world scenarios where limited knowledge about the system…
A Control Theoretical Approach to Online Constrained Optimization
Umberto Casti, Nicola Bastianello, Ruggero Carli +1
In this paper we focus on the solution of online problems with time-varying, linear equality and inequality constraints. Our approach is to design a novel online algorithm by lever…
ADMM-Tracking Gradient for Distributed Optimization over Asynchronous and Unreliable Networks
Guido Carnevale, Nicola Bastianello, Giuseppe Notarstefano +1
In this paper, we propose a novel distributed algorithm for consensus optimization over networks and a robust extension tailored to deal with asynchronous agents and packet losses.…
Forward Dynamics Estimation from Data-Driven Inverse Dynamics Learning
Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli +2
In this paper, we propose to estimate the forward dynamics equations of mechanical systems by learning a model of the inverse dynamics and estimating individual dynamics components…
Learning Control from Raw Position Measurements
Fabio Amadio, Alberto Dalla Libera, Daniel Nikovski +2
We propose a Model-Based Reinforcement Learning (MBRL) algorithm named VF-MC-PILCO, specifically designed for application to mechanical systems where velocities cannot be directly…