About me

I am currently pursuing a PhD in Aeronautics & Astronautics at Stanford University as part of the Autonomous Systems Laboratory under the guidance of Professor Marco Pavone. Generally speaking, my research here attempts to leverage optimization, control theory, machine learning and other computational breakthroughs (e.g. autodiff [1], GPUs [2]) to address the problems of planning and control for complex robotic systems. I am particularly interested in aerial robotics and systems that make and break contact with their environments.

In 2015, I 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, I conducted research on planning and control for small aerial vehicles [3] under the supervision of Professor Russ Tedrake. I was later responsible for control systems development at 3D Robotics.

I had the priviledge of becoming a Siebel Scholar, and receive the Stanford Robotics Center Fellowship supported by FANUC. I cofounded the Stanford Robotics Seminar and proudly TA’ed the first two instances of Principles of Robotic Autonomy.

Publications

  1. Dai, H., Landry, B., Pavone, M., & Tedrake, R. (2020). Counter-Example Guided Synthesis of Neural Network Lyapunov Functions for Piecewise Linear Systems. IEEE Conference on Decision and Control (CDC).
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  2. Landry, B., Lorenzetti, J., Manchester, Z., & Pavone, M. (2019). Bilevel Optimization for Planning through Contact: A Semidirect Method. Int. Symp. on Robotics Research (ISRR).
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  3. Landry, B., Manchester, Z., & Pavone, M. (2019). A Differentiable Augmented Lagrangian Method for Bilevel Nonlinear Optimization. Robotics: Science and Systems (RSS).
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  4. Singh, S., Landry, B., Majumdar, A., Slotine, J.-J. E., & Pavone, M. (2019). Robust Feedback Motion Planning via Contraction Theory. Int. Journal of Robotics Research (IJRR).
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  5. Abtahi, P., Landry, B., Yang, J. J., Pavone, M., Follmer, S., & Landay, J. A. (2019). 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.
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  6. Lorenzetti, J., Landry, B., Singh, S., & Pavone, M. (2019). Reduced Order Model Predictive Control For Setpoint Tracking. European Control Conference (ECC).
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  7. Ichter, B., Landry, B., Schmerling, E., & Pavone, M. (2017). Perception-Aware Motion Planning via Multiobjective Search on GPUs. Int. Symp. on Robotics Research (ISRR).
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  8. Lorenzetti, J., Chen, M., Landry, B., & Pavone, M. (2018). Reach-Avoid Games Via Mixed-Integer Second-Order Cone Programming. Proc. IEEE Conf. on Decision and Control (CDC).
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  9. Landry, B., Chen, M., Hemley, S., & Pavone, M. (2018). Reach-Avoid Problems via Sum-of-Squares Optimization and Dynamic Programming. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems (IROS).
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  10. Landry, B., Deits, R., Florence, P. R., & Tedrake, R. (2016). Aggressive quadrotor flight through cluttered environments using mixed integer programming. 2016 IEEE International Conference on Robotics and Automation (ICRA), 1469–1475.
    pdf - video
  11. Landry, B. (2015). Planning and control for quadrotor flight through cluttered environments [PhD thesis]. Massachusetts Institute of Technology.
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