Francesco Ferracuti

About

Francesco Ferracuti’s research sits at the intersection of assistive robotics, human-robot interaction, and brain-computer interfaces, with a focus on enhancing the autonomy and safety of smart wheelchairs for elderly and disabled users. His major contributions center on developing human-in-the-loop control systems that integrate EEG signals to detect and correct robot navigation errors in real time—particularly when sensors fail or obstacles go undetected. His most-cited work, “Augmenting robot intelligence via EEG signals to avoid trajectory planning mistakes of a smart wheelchair” (24 citations), exemplifies this approach by using neural feedback to prevent collisions. Ferracuti also pioneered a QR-code localization system for mobile robots (24 citations) and a real-time fall detection system using mobile robots and Bluetooth beacons (13 citations). His studies on mental fatigue evaluation during passive and active BCI control (10 citations) further advance practical, safe wheelchair navigation. By combining non-invasive EEG, error-related potential detection, and mobile robotics, Ferracuti’s work directly addresses real-world challenges in ambient assisted living, making assistive technology more responsive, intelligent, and trustworthy for vulnerable populations.

Research Focus

Key Achievements

Top Papers

1. 1
   Augmenting robot intelligence via EEG signals to avoid trajectory planning mistakes of a smart wheelchair

   24 citations · 2021
2. 2
   A QR-code localization system for mobile robots: Application to smart wheelchairs

   24 citations · 2017
3. 3
   A human-in-the-loop approach for enhancing mobile robot navigation in presence of obstacles not detected by the sensory set

   15 citations · 2022
4. 4
   AAL Technologies for Independent Life of Elderly People

   14 citations · 2015
5. 5
   Real-time fall detection system by using mobile robots in smart homes

   13 citations · 2017
6. 6
   Human-in-the-Loop Approach for Enhanced Mobile Robot Navigation

   12 citations · 2022
7. 7
   Mental Fatigue Evaluation for Passive and Active BCI Methods for Wheelchair-Robot During Human-in-the-Loop Control

   10 citations · 2023
8. 8
   Human-in-the-Loop Approach to Safe Navigation of a Smart Wheelchair via Brain Computer Interface

   9 citations · 2021
9. 9
   ErrP Signals Detection for Safe Navigation of a Smart Wheelchair

   8 citations · 2019
10. 10
    Real-Time Mobile Robot Obstacles Detection and Avoidance Through EEG Signals

    4 citations · 2025

Key Collaborators

Contact & Links