activity
20162026
most citedUpper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter

54 citations · 181 across the 20 of their papers we have counts for

collaborators

22 papers

math.AT2026

Discrete Morse Theory for Computing Filtered Cosheaf Homology

Neria Baris

This paper addresses the computation of persistent homology for filtrations of cellular cosheaves over a fixed cell complex, where the algebraic data vary along the filtration whil…

cs.RO2026

Learning Social Robot Navigation By Sensing Human Legs

Alberto Vaglio, Andrea Garulli, Antonio Giannitrapani +2

Robots navigating among pedestrians typically sense their surroundings with a 2D LiDAR mounted close to the ground. At that height, the sensor mostly sees moving legs rather than w…

eess.SY2026

Data-Driven Robust Predictive Control with Interval Matrix Uncertainty Propagation

Renato Quartullo, Andrea Garulli, Mirko Leomanni

This paper presents a new data-driven robust predictive control law, for linear systems affected by unknown-but-bounded process disturbances. A sequence of input-state data is used…

eess.SY2026

Robust Model Predictive Control for Linear Systems with Interval Matrix Model Uncertainty

Renato Quartullo, Andrea Garulli, Mirko Leomanni

This paper proposes a novel robust Model Predictive Control (MPC) scheme for linear discrete-time systems affected by model uncertainty described by interval matrices. The key feat…

eess.SY2025

Time-Optimal Model Predictive Control for Linear Systems with Multiplicative Uncertainties

Renato Quartullo, Andrea Garulli, Mirko Leomanni

This paper presents a time-optimal Model Predictive Control (MPC) scheme for linear discrete-time systems subject to multiplicative uncertainties represented by interval matrices.…

cs.HC2025★ 2 cited

A Comparative Study of Human Motion Models in Reinforcement Learning Algorithms for Social Robot Navigation

Tommaso Van Der Meer, Andrea Garulli, Antonio Giannitrapani +1

Social robot navigation is an evolving research field that aims to find efficient strategies to safely navigate dynamic environments populated by humans. A critical challenge in th…