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Thomas Lew

Thomas Lew

Alumni · now at Toyota Research Institute (TRI)

Thomas is a Ph.D. student in the Department of Aeronautics and Astronautics. He completed his M.Sc. in Robotics at ETH Zurich and his B.Sc. at EPFL, Switzerland. At ETH Zurich, he worked on motion generation for legged robotics with Prof. Hutter, designed control algorithms for the student rocketry team, and worked on terramechanics for ESA's ExoMars rover at RUAG Space. He also interned at NASA JPL with Dr. Agha, where he developed resilient contact-based control algorithms for the DARPA SubT Challenge.

To enable autonomous systems to cope with uncertainty while guaranteeing safety, he is currently developing safe learning-based control and uncertainty-aware planning algorithms.

Publications

19 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. T. Lew, “Uncertainty-Aware Control, Planning, and Learning for Reliable Robotic Autonomy,” Ph.D. dissertation, Stanford University, Dept. of Aeronautics and Astronautics, 2023.
  2. 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.
  3. T. Lew, R. Bonalli, and M. Pavone, “Exact Characterization of the Convex Hulls of Reachable Sets,” Proc. IEEE Conf. on Decision and Control, 2023.
  4. 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. A. Wu, T. Lew, K. Solovey, E. Schmerling, and M. Pavone, “Robust-RRT: Probabilistically-Complete Motion Planning for Uncertain Nonlinear Systems,” Int. Symp. on Robotics Research, 2022.
  2. 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.
  3. A. J. Thorpe, T. Lew, M. M. K. Oishi, and M. Pavone, “Data-Driven Chance Constrained Control using Kernel Distribution Embeddings,” Learning for Dynamics & Control Conference, 2022.
  4. 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.
  5. R. Sinha, S. Sharma, S. Banerjee, T. Lew, R. Luo, S. M. Richards, Y. Sun, E. Schmerling, and M. Pavone, “A System-Level View on Out-of-Distribution Data in Robotics,” 2022.
  6. T. Lew, A. Sharma, J. Harrison, A. Bylard, and M. Pavone, “Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework,” IEEE Transactions on Robotics, vol. 38, no. 5, pp. 2888--2907, 2022.
  7. 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.
2021
  1. J. Schilliger, T. Lew, S. M. Richards, S. Hanggi, M. Pavone, and C. Onder, “Control Barrier Functions for Cyber-Physical Systems and Applications to NMPC,” IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 8623--8630, 2021.
2020
  1. T. Lew and M. Pavone, “Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling,” Conf. on Robot Learning, 2020.
  2. T. Lew, R. Bonalli, and M. Pavone, “Chance-Constrained Sequential Convex Programming for Robust Trajectory Optimization,” European Control Conference, 2020.
  3. 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.