ASL LabStanford University
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Riccardo Bonalli

rbonalli _at_ stanford _dot_ edu

Riccardo Bonalli

Alumni · now at CNRS

Riccardo is a postdoctoral researcher at Stanford’s Department of Aeronautics and Astronautics. He obtained his Ph.D. in Applied Mathematics at Sorbonne Université, Paris in 2018 under a collaboration with ONERA - The French Aerospace Lab, Palaiseau, and received both his B.Sc. in Physical Engineering in 2011 and his M.Sc. in Mathematical Engineering in 2014 from Politecnico di Milano, Milan.

Riccardo’s research interests include differential geometry and Lie groups theory applied to nonlinear control systems, theoretical and numerical optimal control and optimization, homotopy and shooting algorithms, aerospace rendezvous problems, motion planning and trajectory optimization. Under a NASA grant, he is currently focusing on developing fast and robust algorithms for the optimal control of robots operating in microgravity environments.

In his free time, Riccardo enjoys skiing, political philosophy and viticulture.

Awards:

  • 2018 Best Ph.D. thesis at ONERA, TIS Department

Publications

16 publications · full lab bibliography

2024
  1. T. Lew, R. Bonalli, L. Janson, and M. Pavone, “Estimating the convex hull of the image of a set with smooth boundary: error bounds and applications,” Discrete & Computational Geometry, pp. 1--39, 2024.
  2. T. Lew, R. Bonalli, and M. Pavone, “Convex Hulls of Reachable Sets,” IEEE Transactions on Automatic Control, 2024. (Submitted)
  3. T. Lew, R. Bonalli, and M. Pavone, “Sample Average Approximation for Stochastic Programming with Equality Constraints,” SIAM Journal on Optimization, vol. 34, no. 4, pp. 3506--3533, 2024.
2023
  1. R. Bonalli, T. Lew, and M. Pavone, “Analysis of Theoretical and Numerical Properties of Sequential Convex Programming for Continuous-Time Optimal Control,” IEEE Transactions on Automatic Control, vol. 68, no. 8, pp. 4570--4585, 2023.
  2. T. Lew, R. Bonalli, and M. Pavone, “Exact Characterization of the Convex Hulls of Reachable Sets,” Proc. IEEE Conf. on Decision and Control, 2023.
  3. T. Lew, R. Bonalli, and M. Pavone, “Risk-Averse Trajectory Optimization via Sample Average Approximation,” IEEE Robotics and Automation Letters, vol. 9, no. 2, pp. 1500--1507, 2023.
2022
  1. T. Lew, L. Janson, R. Bonalli, and M. Pavone, “A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis,” Learning for Dynamics & Control Conference, 2022.
  2. D. Malyuta, T. P. Reynolds, M. Szmuk, T. Lew, R. Bonalli, M. Pavone, and B. Acikmese, “Convex Optimization for Trajectory Generation,” IEEE Control Systems Magazine, vol. 42, no. 5, pp. 40--113, 2022.
  3. R. Bonalli, T. Lew, and M. Pavone, “Sequential Convex Programming For Non-Linear Stochastic Optimal Control,” ESAIM: Control, Optimisation & Calculus of Variations, vol. 28, 2022.
  4. F. Mahlknecht, J. Alora, S. Jain, E. Schmerling, R. Bonalli, G. Haller, and M. Pavone, “Using Spectral Submanifolds for Nonlinear Periodic Control,” Proc. IEEE Conf. on Decision and Control, 2022.
2021
  1. A. Bylard, R. Bonalli, and M. Pavone, “Composable Geometric Motion Policies using Multi-Task Pullback Bundle Dynamical Systems,” Proc. IEEE Conf. on Robotics and Automation, 2021.
  2. M. P. Chapman, R. Bonalli, K. M. Smith, I. Yang, M. Pavone, and C. J. Tomlin, “Risk-sensitive safety analysis using Conditional Value-at-Risk,” IEEE Transactions on Automatic Control, vol. 67, no. 12, pp. 6521-6536, 2021.
2020
  1. T. Lew, R. Bonalli, and M. Pavone, “Chance-Constrained Sequential Convex Programming for Robust Trajectory Optimization,” European Control Conference, 2020.
  2. S. Banerjee, T. Lew, R. Bonalli, A. Alfaadhel, I. A. Alomar, H. M. Shageer, and M. Pavone, “Learning-based Warm-Starting for Fast Sequential Convex Programming and Trajectory Optimization,” IEEE Aerospace Conference, 2020.
2019
  1. R. Bonalli, A. Bylard, A. Cauligi, T. Lew, and M. Pavone, “Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach,” Robotics: Science and Systems, 2019.
  2. R. Bonalli, A. Cauligi, A. Bylard, and M. Pavone, “GuSTO: Guaranteed Sequential Trajectory Optimization via Sequential Convex Programming,” Proc. IEEE Conf. on Robotics and Automation, 2019.