Pre-prints

Continuously Optimizing Radar Placement with Model Predictive Path Integrals

Michael Potter, Shuo Tang, Paul Ghanem, Milica Stojanovic, Pau Closas, Murat Akcakaya, Ben Wright, Marius Necsoiu, Deniz Erdogmus, Michael Everett, Tales Imbiriba

2024 (in review)

Paper    

LiDAR Inertial Odometry And Mapping Using Learned Registration-Relevant Features

Zihao Dong, Jeff Pflueger, Leonard Jung, David Thorne, Philip R. Osteen, Christa S. Robison, Brett T. Lopez, Michael Everett

2024 (in review)

Paper     Code    

Robust Survival Analysis with Adversarial Regularization

Michael Potter, Stefano Maxenti, Michael Everett

2023 (in review)

Paper     Code    

Peer-Reviewed Publications

Collision Avoidance Verification of Multiagent Systems with Learned Policies

Zihao Dong, Shayegan Omidshafiei, Michael Everett

IEEE Control Systems Letters (L-CSS), 2024

Paper     Code    

EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy

Xiaoyi Cai, Siddharth Ancha, Lakshay Sharma, Philip R. Osteen, Bernadette Bucher, Stephen Phillips, Jiuguang Wang, Michael Everett, Nicholas Roy, Jonathan P. How

IEEE Transactions on Robotics (TRO), 2024

Paper     Code    

RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation

Lakshay Sharma, Michael Everett, Donggun Lee, Xiaoyi Cai, Philip Osteen, Jonathan P. How

IEEE International Conference on Robotics and Automation (ICRA), 2023

Paper    

A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops

Nicholas Rober, Michael Everett, Songan Zhang, Jonathan P. How

American Controls Conference (ACC), 2023

Paper     Code    

Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems

Nicholas Rober, Sydney M. Katz, Chelsea Sidrane, Esen Yel, Michael Everett, Mykel J. Kochenderfer, Jonathan P. How

IEEE Open Journal of Control Systems (OJ-CSYS): Special Section: Formal Verification and Synthesis of Cyber-Physical Systems, 2023

Paper     Code    

Principles and Guidelines for Evaluating Social Robot Navigation Algorithms

Anthony Francis, Claudia Pérez-d'Arpino, Chengshu Li, Fei Xia, Alexandre Alahi, Rachid Alami, Aniket Bera, Abhijat Biswas, Joydeep Biswas, Rohan Chandra, Hao-Tien Lewis Chiang, Michael Everett, Sehoon Ha, Justin Hart, Jonathan P How, Haresh Karnan, Tsang-Wei Edward Lee, Luis J Manso, Reuth Mirksy, Soeren Pirk, Phani Teja Singamaneni, Peter Stone, Ada V Taylor, Peter Trautman, Nathan Tsoi, Marynel Vazquez, Xuesu Xiao, Peng Xu, Naoki Yokoyama, Alexander Toshev, Roberto Martin-Martin

ACM Transactions on Human-Robot Interaction (T-HRI), 2023 (accepted)

Paper     Code    

DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops

Michael Everett, Rudy Bunel, Shayegan Omidshafiei

IEEE Control Systems Letters (L-CSS), 2023

Paper     Code    

Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments

Xiaoyi Cai, Michael Everett, Lakshay Sharma, Philip R. Osteen, Jonathan P. How

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023

Paper     Code    

Backward Reachability Analysis of Neural Feedback Loops

Nicholas Rober, Michael Everett, Jonathan P. How

IEEE Conference on Decision and Control (CDC), 2022

Also presented in 1st Workshop on Formal Verification of Machine Learning, ICML 2022.

Runner-Up: Best Paper Award (WFVML 2022)

IEEE TC on Aerospace Control: Best Student Paper Award

Paper     Code    

Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning

Michael Everett*, Björn Lütjens*, Jonathan P. How

IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022

Paper    

Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map

Xiaoyi Cai, Michael Everett, Jonathan Fink, Jonathan P. How

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022

Paper     Code    

Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube-MPC

Andrea Tagliabue, Dong-Ki Kim, Michael Everett, Jonathan P. How

IEEE International Conference on Robotics and Automation (ICRA), 2022

Paper     Video    

Influencing Long-Term Behavior in Multiagent Reinforcement Learning

Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How

Conference on Neural Information Processing Systems (NeurIPS), 2022

Also presented in ICLR Workshop on Gamification and Multiagent Solutions, 2022

Paper     Code    

FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments

Jesus Tordesillas, Brett T. Lopez, Michael Everett, Jonathan P. How

IEEE Transactions on Robotics (TRO), 2022

Paper     Code     Video    

Robustness Analysis of Neural Networks via Efficient Partitioning with Applications in Control Systems

Michael Everett, Golnaz Habibi, Jonathan P. How

IEEE Control Systems Letters (L-CSS), 2021

Also presented in American Controls Conference (ACC) Invited Session on Learning, Optimization, and Control for Safety-critical Systems, May, 2021.

Paper     Code     Video    

Reachability Analysis of Neural Feedback Loops

Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How

IEEE Access, 2021

Paper     Code    

Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning

Michael Everett, Yu Fan Chen, Jonathan P. How

IEEE Access: Special Section on Real-Time Machine Learning Applications in Mobile Robotics, 2021

Editors' Top 5 Published Article Selections for 2021

Featured Article of the Week (March 2021)

Paper     Code: [ Pre-Trained ROS Package Training Environment RL Training Code ]   

Neural Network Verification in Control (Tutorial)

Michael Everett

IEEE Conference on Decision and Control (CDC), 2021

Paper     Code     Video    

Where to go next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic Environments

Bruno Brito, Michael Everett, Jonathan P. How, Javier Alonso-Mora

IEEE Robotics and Automation Letters (RA-L), 2021

Also presented in ICRA, May, 2021.

Paper     Code     Video    

Efficient Reachability Analysis for Closed-Loop Systems with Neural Network Controllers

Michael Everett, Golnaz Habibi, Jonathan P. How

IEEE International Conference on Robotics and Automation (ICRA), 2021

Also presented in International Conference on Learning Representations (ICLR) Workshop on Robust and Reliable Machine Learning in the Real World, May, 2021.

Paper     Code     Video    

Multi-Agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning

Samaneh Hosseini Semnani, Hugh Liu, Michael Everett, Anton de Ruiter, Jonathan P How

IEEE Robotics and Automation Letters (RA-L), 2020

Paper    

Planning Beyond The Sensing Horizon Using a Learned Context

Michael Everett, Justin Miller, Jonathan P. How

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019

Winner: Best Paper Award on Cognitive Robotics

Paper     Code     Video    

Certified Adversarial Robustness for Deep Reinforcement Learning

Björn Lütjens, Michael Everett, Jonathan P. How

Conference on Robot Learning (CoRL), 2019

Paper     Video    

R-MADDPG for Partially Observable Environments and Limited Communication

Rose E Wang, Michael Everett, Jonathan P. How

ICML Workshop: Reinforcement Learning for Real Life, 2019

Code    

Safe Reinforcement Learning with Model Uncertainty Estimates

Björn Lütjens, Michael Everett, Jonathan P. How

IEEE International Conference on Robotics and Automation (ICRA), 2019

Paper    

Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning

Michael Everett, Yu Fan Chen, Jonathan P. How

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018

Paper     Video    

Socially Aware Motion Planning with Deep Reinforcement Learning

Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017

Winner: Best Student Paper

Finalist: Best Paper Award on Cognitive Robotics

Paper     Video    

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations

Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett T Lopez, Christopher Amato, Miao Liu, Jonathan P How, John Vian

IEEE International Conference on Robotics and Automation (ICRA), 2017

Paper     Video    

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces

Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P How, John Vian

IEEE International Conference on Robotics and Automation (ICRA), 2017

Paper    

Decentralized Non-Communicating Multiagent Collision Avoidance with Deep Reinforcement Learning

Yu Fan Chen, Miao Liu, Michael Everett, Jonathan P. How

IEEE International Conference on Robotics and Automation (ICRA), 2017

Finalist: Best Multi-Robot Systems Paper

Paper     Video    

Theses

Algorithms for Robust Autonomous Navigation in Human Environments

Michael Everett

PhD Thesis, 2020

MIT Department of Mechanical Engineering

Video    

Robot Designed for Socially Acceptable Navigation

Michael Everett

SM Thesis, 2017

MIT Department of Mechanical Engineering