Francesco Giovannini

About

Francesco Giovannini is a robotics researcher whose work bridges the critical gap between robotic manipulation and intelligent control. His primary research areas include mobile robotics, tactile sensing, and autonomous grasping, with a particular focus on enabling robots to interact more effectively with unstructured environments. His most cited work, a comprehensive 2022 review on mobile robot path planning and multirobot control (46 citations), provides a foundational resource for researchers navigating this complex field. Giovannini made significant contributions to tactile sensing through his design of a novel fingertip for the iCub humanoid robot (42 citations), addressing the longstanding challenge of integrating deformable sensors into robotic hands. He has also advanced the application of machine learning in robotics, using genetic algorithms to optimize stable grasping and developing Gaussian process models to compensate for tactile sensor hysteresis—a key innovation for accurate force estimation during manipulation. With additional work in predictive maintenance, Giovannini demonstrates a versatile approach to creating more capable, perceptive, and reliable robotic systems for real-world applications.

Research Focus

Key Achievements

Top Papers

1. 1
   Mobile robots path planning and mobile multirobots control: A review

   46 citations · 2022
2. 2
   A new design of a fingertip for the iCub hand

   42 citations · 2015
3. 3
   Genetic Algorithms for Stable Robot Grasping

   8 citations · 2022
4. 4
   Predictive Maintenance Based on Machine Learning Model

   7 citations · 2022
5. 5
   Compensation for tactile hysteresis using Gaussian process with sensory Markov property

   6 citations · 2014
6. 6
   Contact force estimation from flexible tactile sensor values considering hysteresis by Gaussian process

   2 citations · 2014

Key Collaborators

Contact & Links