I'm a Research Engineer at IIT under the research line Soft Robotics for Human Cooperation and Rehabilitation. I'm also a Collaborator at Centro di Ricerca E. Piaggio - University of Pisa.
I received the Master degree in Robotics and Automation Engineering and the Bachelor degree in Computer Engineering, both from the University of Pisa.
My main research interests are in the field of Robotics, Elctronic systems, Embedded systems, Human Robot Interaction and Prosthetics and Rehabilitation. In these years, I designed, developed and realized many robotic devices, I just cite here the most important contributions and my role:
- Design, development and realization of electronics and hardware components for upper-limb prosthetic devices within the EU funded SoftPro project
- Firmware framework development for the use and validation of the prosthetic platform “SoftHand Pro”
- Firmware and electronics development of the following devices:
- FYD-pad: design and realization of a tactile display for softness and texture rendering in human-robot and teleoperation applications (WEARHAP project)
- Pisa/IIT SoftHand, SoftHand 2 devices (ERC SoftHand Pro-H, ERC SoftHands and SoMa projects)
- WALK-MAN humanoid robot (WALK-MAN project)
- SoftGlove: firmware implementation of an IMU based robotic glove for reactive grasp applications (SoMa project)
Work activities within the following EU/ERC projects:
- ERC Natural BionicS: Natural Integration of Bionic Limbs via Spinal Interfacing
- SoftPro: Synergy-Based Open-Source Foundations and Technologies for Prosthetics and rehabilitation
- DYSTURBANCE: Dynamic and static pusher to benchmark balance (EUROBENCH)
- ERC SoftHand Pro-H: A Soft Synergy-based Hand Prosthesis with Hybrid Control
- SOMA: Soft-bodied intelligence for Manipulation
- THING: subTerranean Haptic INvestiGator Project
- Walk-Man: Whole Body Adaptive Locomotion and Manipulation
- ERC SoftHand: a theory of soft synergies for a new generation of artificial hands
- WEARHAP: Wearable Haptics for Humans and Robots
- SAPHARI: Safe and Autonomous Physical Human-Aware Robot Interaction
- THE: The Hand Embodied
- PACMAN: Probabilistic and Compositional Representations of Objects for Robotic Manipulation
Most important competitions I participated and achievements I reached:
- "CYBATHLON Prosthesis Series" with "SoftHand Pro" team from IIT and University of Pisa,May 2019, Karlsruhe, Germany, 2nd place, Participation as firmware and electronics expert as team member in Powered ARM Prosthesis Race held at CYBATHLON Prosthesis Series in Karlsruhe (Germany). The CYBATHLON is a unique championship in which people with physical disabilities compete against each other to complete everyday tasks using state-of-the-art technical assistance systems.
- "CYBATHLON Experience 2018" with "SoftHand Pro" team from IIT and University of Pisa,Sep 2018, Dusseldorf, Germany. Participation as firmware and electronics expert as team member in Powered ARM Prosthesis Race held at CYBATHLON Experience at REHACARE Conference in Dusseldorf (Germany).
- “A Novel Tactile Display for Softness and Texture Rendering in Tele-Operation Tasks”, Jun 2015, Regular paper at World Haptics Conference, Evanston, Illinois, U.S.A. This work presents FYD-pad, a fabric-based yielding tactile display for softness and texture rendering. The system exploits the control of two motors to modify both the stretching state of the elastic fabric for softness rendering and to convey texture information on the basis of accelerometer-based data. At the same time, the measurement of the contact area can be used to control remote or virtual robots. In this paper, the architecture of FYD-pad and the techniques used for softness and texture reproduction were discussed as well as experiments with humans to show the effectiveness of the device in delivering tactile information.
- "Amazon Picking Challenge” with “Research Center E.Piaggio” team from University of Pisa, May 2015, International Conference on Robotics and Automation 2015 (ICRA), Seattle, Washington, U.S.A. This competition challenged teams to build their own robot hardware and software that could attempt simplified versions of the general task of picking items from shelves. The robots were presented with a stationary lightly populated inventory shelf and were asked to pick a subset of the products and put them on a table. The challenge combined object recognition, pose recognition, grasp planning, compliant manipulation, motion planning, task planning, task execution, and error detection and recovery.