FUSCO , Franco

Visual Servoing has been widely investigated inthe last decades as it provides a powerful strategy for robotcontrol. Thanks to the direct feed-back from a set of sensors,it allows to reduce the impact of some modeling errors and toperform tasks even in uncertain environments. The commonlyexploited approach in this...

This paper proposes new prediction models for Visual Predictive Control that can lead to both better motions in the feature space and shorter sensor trajectories in 3D. Contrarily to existing first-order models based only on the interaction matrix, it is proposed to integrate acceleration information provided by second-order models. This allows...

Solving Direct Shooting Model Predictive Control (MPC) optimization problems online can be computationally expensive if a large horizon is used while also maintaining a dense time sampling. In these cases, it is accepted that tradeoffs between computational load and performances should be sought in order to meet real-time feasibility...

Model Predictive Control (MPC) while being a very effective control technique can become computationally demanding when a large prediction horizon is selected. To make the problem more tractable, one technique that has been proposed in the literature makes use of control input parameterizations to decrease the numerical complexity of nonlinear...

Machine learning is often cited as a new paradigm in control theory, but is also often viewed as empirical and less intuitive for students than classical model-based methods. This is particularly the case for reinforcement learning, an approach that does not require any mathematical model to drive a system inside an unknown environment. This...