Spencer M. Richards
Alumni · now at Toyota Research Institute (TRI)
Spencer is a Ph.D. student in the Aeronautics and Astronautics Department. Currently, he focuses on learning-based control for robotic systems. He works to create agents that learn safely and efficiently in the real world by leveraging tools from both control theory and machine learning. In general, he is interested in determining theoretic safety guarantees for dynamical systems, and how they translate into practice.
Previously, he completed his M.Sc. in Robotics, Systems, and Control at ETH Zurich, and his B.ASc. in Engineering Science (with a Major in Aerospace Engineering) at the University of Toronto. At ETH Zurich, he conducted his Master’s thesis on safe reinforcement learning with Felix Berkenkamp and Prof. Andreas Krause. He also worked on theory for mobility-on-demand systems with Claudio Ruch and Prof. Emilio Frazzoli. At the University of Toronto Institute for Aerospace Studies (UTIAS), he worked on state estimation for drones during his Bachelor’s thesis with Prof. Angela Schoellig. As an intern at Verity Studios, he developed autonomous flying machines for live entertainment with Prof. Raffaello D’Andrea.
Publications
9 publications · full lab bibliography
- S. M. Richards, J. J. Slotine, N. Azizan, and M. Pavone, “Learning Control-Oriented Dynamical Structure from Data,” Int. Conf. on Machine Learning, 2023. (In Press)
- S. M. Richards, “Control-Oriented Learning for Dynamical Systems,” Ph.D. dissertation, Stanford University, Dept. of Aeronautics and Astronautics, 2023.
- S. M. Richards, N. Azizan, J. J. Slotine, and M. Pavone, “Control-Oriented Meta-Learning,” Int. Journal of Robotics Research, vol. 42, no. 10, pp. 777--797, 2023.
- 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.
- R. Sinha, J. Harrison, S. M. Richards, and M. Pavone, “Adaptive Robust Model Predictive Control via Uncertainty Cancellation,” IEEE Transactions on Automatic Control, 2022. (In Press)
- R. Sinha, J. Harrison, S. M. Richards, and M. Pavone, “Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty,” American Control Conference, 2022.
- 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.
- S. M. Richards, N. Azizan, J. J. Slotine, and M. Pavone, “Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems,” Robotics: Science and Systems, 2021.
- S. Singh, S. M. Richards, V. Sindhwani, J. J. E. Slotine, and M. Pavone, “Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization,” Int. Journal of Robotics Research, vol. 40, no. 10--11, pp. 1123-1150, 2021.