Aerospace Controls Laboratory

Website  /  Google Scholar
atagliab [at] mit [dot] edu
31-232A

Education

• Ph.D. in Aeronautics and Astronautics, MIT, 2019 - current
• M.S. in Robotics, Systems and Control, ETH Zurich (Switzerland), 2018
• B.S. in Automation Engineering, Politecnico di Milano (Italy), 2015

Research Interests

• Neural-Inspired Methods for Sensing and Control on MAVs
• Data-Driven, Resilient Sensing and State Estimation
• Imitation and Reinforcement Learning for Robust Flight Control
• Multi-Agent Planning and Control in Communication-Denied Environments

Projects

Efficient Learning of Neural Network Policies via Imitation Learning and Tube MPC
Andrea Tagliabue, Dong-Ki Kim, Michael Everett, 2022

Use a Robust Tube variant of MPC to efficiently learn Neural Network policies via Imitation Learning.

Lidar-Inertial Observability-Aware Navigator
Andrea Tagliabue, Jesus Tordesillas Torres, Xiaoyi (Jeremy) Cai, Ali-akbar Ahga-mohammadi, 2020

This work presents the Lidar-Inertial Observability-Aware Navigator used at the DARPA Subt. challenge.