Olga Napolitano — accepted AI-conference papers

2022

Information-Aware Lyapunov-Based MPC in a Feedback-Feedforward Control Strategy for Autonomous Robots

Olga Napolitano, Daniele Fontanelli, Lucia Pallottino, Paolo Salaris

RA-L 2022

This letter proposes a feedback-feedforward control scheme that combines the benefits of an online active sensing control strategy (the feedforward control component) to maximize the information needed for correctly executing the desired task, with a Lyapunov-based control strategy (the feedback con

Cited by 10 Source ↗Scholar ↗

2021

Gramian-based optimal active sensing control under intermittent measurements

Olga Napolitano, Daniele Fontanelli, Lucia Pallottino, Paolo Salaris

ICRA 2021poster

This paper proposes an online optimal perception-aware strategy meant to maximize the information collected along the trajectory via the available measurements while simultaneously minimizing the negative effects of actuation/process noise. Indeed, in several robotic applications, the actuation/proc…

Cited by 14 Source ↗Scholar ↗