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Joseph Lorenzetti

jlorenze _at_ stanford _dot_ edu

Joseph Lorenzetti

Alumni · now at Zoox, Inc.

Joseph Lorenzetti is a Ph.D. candidate in the Aeronautics & Astronautics department, where he also received his Master's degree in 2018. Prior to his studies at Stanford, Joseph graduated with highest distinction from Purdue University with a B.S. in Aeronautical and Astronautical Engineering. He has also held internships with SpaceX, NASA AFRC, and GE Aviation.

Joseph's research interests include robotics, control theory, and trajectory optimization. His current project focuses on the use of model predictive control techniques to control infinite dimensional systems, with applications to soft robotics and autonomous aircraft control. He is supported by the National Defense Science and Engineering Graduate (NDSEG) Fellowship.

Awards:

  • National Defense Science and Engineering Graduate (NDSEG) Fellowship
  • 2018 Nicholas J. Hoff Award for Outstanding Master's Degree Student

Publications

11 publications · full lab bibliography

2022
  1. A. McClellan, J. Lorenzetti, M. Pavone, and C. Farhat, “A Physics-Based Digital Twin for Model Predictive Control of Autonomous Unmanned Aerial Vehicle Landing,” Philosophical Transactions of the Royal Society A, vol. 380, 2022.
  2. J. Lorenzetti, A. McClellan, C. Farhat, and M. Pavone, “Linear Reduced-Order Model Predictive Control,” IEEE Transactions on Automatic Control, vol. 67, no. 11, pp. 5980--5995, 2022.
2021
  1. J. Lorenzetti, “Reduced Order Model Predictive Control of High-Dimensional Systems,” Ph.D. dissertation, Stanford University, Dept. of Aeronautics and Astronautics, 2021.
  2. S. Tonkens, J. Lorenzetti, and M. Pavone, “Soft Robot Optimal Control Via Reduced Order Finite Element Models,” Proc. IEEE Conf. on Robotics and Automation, 2021.
2020
  1. J. Lorenzetti and M. Pavone, “Error Bounds for Reduced Order Model Predictive Control,” Proc. IEEE Conf. on Decision and Control, 2020.
  2. J. Lorenzetti and M. Pavone, “A Simple and Efficient Tube-based Robust Output Feedback Model Predictive Control Scheme,” European Control Conference, 2020.
  3. A. McClellan, J. Lorenzetti, M. Pavone, and C. Farhat, “Projection-based Model Order Reduction for Flight Dynamics and Model Predictive Control,” AIAA Scitech Forum, 2020.
  4. J. Lorenzetti, A. McClellan, C. Farhat, and M. Pavone, “UAV Aircraft Carrier Landing Using CFD-Based Model Predictive Control,” AIAA Scitech Forum, 2020.
2019
  1. B. Landry, J. Lorenzetti, Z. Manchester, and M. Pavone, “Bilevel Optimization for Planning through Contact: A Semidirect Method,” Int. Symp. on Robotics Research, 2019.
  2. J. Lorenzetti, B. Landry, S. Singh, and M. Pavone, “Reduced Order Model Predictive Control For Setpoint Tracking,” European Control Conference, 2019.
2018
  1. J. Lorenzetti, M. Chen, B. Landry, and M. Pavone, “Reach-Avoid Games Via Mixed-Integer Second-Order Cone Programming,” Proc. IEEE Conf. on Decision and Control, 2018.