Francesco Ferrari

About

Francesco Ferrari’s research navigates the critical intersection of human-robot interaction, assistive robotics, and the psychological implications of automation. His most influential work, “Blurring Human–Machine Distinctions” (298 citations), probes how anthropomorphic social robots threaten human distinctiveness—a foundational contribution to the ethics and design of social AI. In assistive robotics, Ferrari has pioneered safer, more intuitive mobility aids for older adults. His ACANTO interactive guidance system (48 citations) and subsequent papers on passive robotic walkers (18 and 15 citations) introduce authority-sharing and haptic-braking strategies that ensure user-led control while maintaining safety in crowded environments. He also advanced preference learning through observational inverse reinforcement learning (23 citations), enabling robots to adapt to individual user behaviors. Ferrari’s work balances technical innovation with deep human-centered concerns, making him a key voice in debates on hybrid societies and aging populations. His contributions continue to shape how robots can support—rather than supplant—human autonomy.

Research Focus

Key Achievements

Top Papers

1. 1
   Blurring Human–Machine Distinctions: Anthropomorphic Appearance in Social Robots as a Threat to Human Distinctiveness

   298 citations · 2016
2. 2
   Human–Robot Interaction Analysis for a Smart Walker for Elderly: The ACANTO Interactive Guidance System

   48 citations · 2019
3. 3
   Preference Learning in Assistive Robotics: Observational Repeated Inverse Reinforcement Learning

   23 citations · 2018
4. 4
   Simulating Passivity for Robotic Walkers via Authority-Sharing

   18 citations · 2018
5. 5
   Combining Haptic and Bang-Bang Braking Actions for Passive Robotic Walker Path Following

   15 citations · 2019
6. 6
   Toward a Hybrid Society

   10 citations · 2016

Key Collaborators

Contact & Links