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Michael Everett Pre-prints Verification of Visual Controllers via Compositional Geometric Transformations Alexander Estornell, Leonard Jung, Michael Everett 2025 (in review)
Temporal Point Process Modeling of Aggressive Behavior Onset in Psychiatric Inpatient Youths with Autism Michael Potter, Michael Everett, Ashutosh Singh, Georgios Stratis, Yuna Watanabe, Ahmet Demirkaya, Deniz Erdogmus, Tales Imbiriba, Matthew S Goodwin 2025 (in review)
Learning Smooth State-Dependent Traversability from Dense Point Clouds Zihao Dong, Alan Papalia, Leonard Jung, Alenna Spiro, Phil Osteen, Christa Robison, Michael Everett 2025 (in review)
Peer-Reviewed Publications Chance-Constrained Convex MPC for Robust Quadruped Locomotion Under Parametric and Additive Uncertainties Ananya Trivedi, Sarvesh Prajapati, Mark Zolotas, Michael Everett, Taskin Padir IEEE Robotics and Automation Letters (RA-L), 2025
Real-Time Adaptive Motion Planning via Point Cloud-Guided, Energy-Based Diffusion and Potential Fields Wondmgezahu Teshome, Kian Behzad, Octavia Camps, Michael Everett, Milad Siami, Mario Sznaier IEEE Robotics and Automation Letters (RA-L), 2025 (accepted)
Active Learning For Repairable Hardware Systems With Partial Coverage Michael Potter, Beyza Kalkanlı, Deniz Erdoğmuş, Michael Everett Reliability, Availability, Maintainability and Safety (R.A.M.S.) - Europe, 2025 (accepted)
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 IEEE Transactions on Aerospace and Electronic Systems (T-AES), 2025
Robust Survival Analysis with Adversarial Regularization Michael Potter, Stefano Maxenti, Michael Everett IEEE International Conference on Healthcare Informatics (ICHI), 2025
Adversarial Decoy Placement for Strategic State Perturbations in Artificial Intelligence Driven Defense Armita Kazeminajafabadi, Michael Everett, Tian Lan, Nathaniel D. Bastian, Mahdi Imani IEEE Conference on Decision and Control (CDC), 2025 (accepted)
Continuous Contingency Planning with MPPI within MPPI Leonard Jung, Alexander Estornell, Michael Everett Learning for Dynamics and Control Conference (L4DC), 2025
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), 2025
A Hybrid Framework for Efficient Koopman Operator Learning Alexander Estornell*, Leonard Jung*, Alenna Spiro*, Mario Sznaier, Michael Everett IEEE Conference on Decision and Control (CDC), 2025 (accepted)
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 IEEE International Conference on Robotics and Automation (ICRA), 2025
Learning Verifiable Control Policies Using Relaxed Verification Puja Chaudhury, Alexander Estornell, Michael Everett IEEE Conference on Decision and Control (CDC), 2025 (accepted)
Collision Avoidance Verification of Multiagent Systems with Learned Policies Zihao Dong, Shayegan Omidshafiei, Michael Everett IEEE Control Systems Letters (L-CSS), 2024
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
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
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
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
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
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
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
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
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
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
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
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
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.
Reachability Analysis of Neural Feedback Loops Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How IEEE Access, 2021
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)
Neural Network Verification in Control (Tutorial) Michael Everett IEEE Conference on Decision and Control (CDC), 2021
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.
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.
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
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
Certified Adversarial Robustness for Deep Reinforcement Learning Björn Lütjens, Michael Everett, Jonathan P. How Conference on Robot Learning (CoRL), 2019
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
Safe Reinforcement Learning with Model Uncertainty Estimates Björn Lütjens, Michael Everett, Jonathan P. How IEEE International Conference on Robotics and Automation (ICRA), 2019
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
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
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
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
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
Theses Algorithms for Robust Autonomous Navigation in Human Environments Michael Everett PhD Thesis, 2020 MIT Department of Mechanical Engineering
Robot Designed for Socially Acceptable Navigation Michael Everett SM Thesis, 2017 MIT Department of Mechanical Engineering
