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Benoit Landry

ben _dot_ acc _dot_ landry _at_ gmail _dot_ com

Benoit Landry

Alumni · now at Apple

Benoit is currently pursuing a Ph.D. in the department of Aeronautics and Astronautics. He received a Bachelor of Science and a Master of Engineering in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (minoring in Science, Technology and Society). At MIT, Benoit conducted research on planning and control for small aerial vehicles under the supervision of Professor Russ Tedrake. He was later responsible for control systems development at 3D Robotics. Generally speaking, Benoit’s research attempts to leverage computational breakthroughs (e.g. autodiff, modern solvers, GPU’s) to address the problems of planning and control for complex robotic systems. He is particularly interested in aerial robotics and systems that make and break contact with their environments.

Awards:

  • Siebel Foundation Scholarship, 2014
  • Stanford Robotics Center Fellowship

Publications

13 publications · full lab bibliography

2023
  1. S. Singh, B. Landry, A. Majumdar, J. J. E. Slotine, and M. Pavone, “Robust Feedback Motion Planning via Contraction Theory,” Int. Journal of Robotics Research, vol. 42, no. 9, pp. 655--688, 2023.
2021
  1. B. Landry, H. Dai, and M. Pavone, “SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions,” Learning for Dynamics & Control Conference, 2021.
  2. S. Roelofs, B. Landry, M. K. Jalil, A. Martin, S. Koppaka, S. K. Y. Tang, and M. Pavone, “Vision-based Autonomous Disinfection of High Touch Surfaces in Indoor Environments,” Int. Conf. on Control, Automation and Systems, 2021.
  3. H. Dai, B. Landry, L. Yang, M. Pavone, and R. Tedrake, “Lyapunov-Stable Neural-Network Control,” Robotics: Science and Systems, 2021.
  4. B. Landry, “Differentiable and Bilevel Optimization for Control in Robotics,” Ph.D. dissertation, Stanford University, Dept. of Aeronautics and Astronautics, 2021.
2020
  1. H. Dai, B. Landry, M. Pavone, and R. Tedrake, “Counter-Example Guided Synthesis of Neural Network Lyapunov Functions for Piecewise Linear Systems,” Proc. IEEE Conf. on Decision and Control, 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. B. Landry, Z. Manchester, and M. Pavone, “A Differentiable Augmented Lagrangian Method for Bilevel Nonlinear Optimization,” Robotics: Science and Systems, 2019.
  3. J. Lorenzetti, B. Landry, S. Singh, and M. Pavone, “Reduced Order Model Predictive Control For Setpoint Tracking,” European Control Conference, 2019.
  4. P. Abtahi, B. Landry, J. J. Yang, M. Pavone, S. Follmer, and J. A. Landay, “Beyond The Force: Using Quadcopters to Appropriate Objects and the Environment for Haptics in Virtual Reality,” ACM CHI Conf. on Human Factors in Computing Systems, 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.
  2. B. Landry, M. Chen, S. Hemley, and M. Pavone, “Reach-Avoid Problems via Sum-of-Squares Optimization and Dynamic Programming,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2018.
2017
  1. B. Ichter, B. Landry, E. Schmerling, and M. Pavone, “Perception-Aware Motion Planning via Multiobjective Search on GPUs,” Int. Symp. on Robotics Research, 2017.