Francesco Tassi, MSc
Human-Robot Interaction, Optimal Control, redundant robots
Center for Robotics and Intelligent Systems (CRIS),
Istituto Italiano di Tecnologia (IIT)
Via S. Quirico, 19d, 16163, Genova, Italy
Francesco received his Master degree in Mechanical Engineering, from Politecnico di Milano in 2018. He developed his MSc thesis at the Jet Propulsion Laboratory (JPL) California, where he worked on the application of Model Predictive Control (MPC) for the realization of distributed space-based robotic swarms. He was for one year a research fellow at Consiglio Nazionale delle Ricerche (CNR) in the automation and robotics division. He is currently pursuing a PhD at the Human-Robot Interfaces and Interaction Laboratory (HRII) of Istituto Italiano di Tecnologia (IIT) with Politecnico di Milano (expected to finish in 2023), working on optimal control for redundant robots. He is currently involved in Horizon-2020 project SOPHIA and ERC project Ergo-Lean.
Francesco aims to provide a synergetic framework that fluently integrates action recognition at the control level. Therefore, an appropriate control logic should be capable of fully exploiting Cobots redundancy. This is possible by defining multiple priority levels of a stack of tasks through Hierarchical Quadratic Programming (HQP), which solves multiple Quadratic Programming (QP) problems, establishing strict non-conflicting priorities.