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Michael Everett
Alum
GitHub
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Website
mfe [at] mit [dot] edu
31-235C
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Ph.D. in Mechanical Engineering, MIT, 2020
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S.M. in Mechanical Engineering, MIT, 2017
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S.B. in Mechanical Engineering, MIT, 2015
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Robust Learning
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Collision Avoidance
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Motion Planning
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Backward Reachability for Neural Feedback Loops
Nicholas Rober,
Michael Everett,
2022
This project developed a backward reachability strategy to certify safety for systems controlled by neural networks
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Efficient Learning of Neural Network Policies via Imitation Learning and Tube MPC
Andrea Tagliabue,
Dong-Ki Kim,
Michael Everett,
2022
Use a Robust Tube variant of MPC to efficiently learn Neural Network policies via Imitation Learning.
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Risk-Aware Off-Road Navigation Leveraging Semantics
Xiaoyi (Jeremy) Cai,
Michael Everett,
2022
Use semantics of the environment to infer terrain traversability based on history of speed data.
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Certified Adversarial Robustness for Deep RL
Michael Everett,
Björn Lütjens,
2020
This project develops deep RL algorithms that are robust to an adversarial perturbation in the observation space
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Self-Driving Delivery Robot
Michael Everett,
Justin Miller (Ford),
2019
This project develops planning algorithms to enable autonomous navigation in the "last 100m" for delivery robots
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Socially Acceptable Navigation
Michael Everett,
Steven Chen,
2019
Collision avoidance algorithm using Deep RL.
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Robust and Interpretable RL for Navigation in Pedestrian Crowds
Björn Lütjens,
Michael Everett,
2018
Deep neural networks can fail overconfidently on novel observations. This work pioneers a reinforcement learning framework that reasons about the predictive confidence and is more robust to novel observations.
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