Posts by Collection
portfolio
publications
 | Decentralized Non-Communicating Multiagent Collision Avoidance with Deep Reinforcement LearningYu Fan Chen, Miao Liu, Michael Everett, Jonathan P. HowIEEE International Conference on Robotics and Automation (ICRA) 2017Paper |
 | Scalable accelerated decentralized multi-robot policy search in continuous observation spacesShayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P How, John VianIEEE International Conference on Robotics and Automation (ICRA) 2017Paper |
 | Semantic-level decentralized multi-robot decision-making using probabilistic macro-observationsShayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett T Lopez, Christopher Amato, Miao Liu, Jonathan P How, John VianIEEE International Conference on Robotics and Automation (ICRA) 2017Paper |
 | Socially Aware Motion Planning with Deep Reinforcement LearningYu Fan Chen, Michael Everett, Miao Liu, Jonathan P. HowIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2017Paper |
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 | Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement LearningMichael Everett, Yu Fan Chen, Jonathan P. HowIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018Paper |
 | Planning Beyond The Sensing Horizon Using a Learned ContextMichael Everett, Jonathan P. HowMachine Learning in Robot Motion Planning Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018 |
| Safe Reinforcement Learning with Model Uncertainty EstimatesBjörn Lütjens, Michael Everett, Jonathan P. HowMachine Learning in Robot Motion Planning Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018Paper |
 | Safe Reinforcement Learning with Model Uncertainty EstimatesBjörn Lütjens, Michael Everett, Jonathan P. HowIEEE International Conference on Robotics and Automation (ICRA) 2019Paper |
 | R-MADDPG for Partially Observable Environments and Limited CommunicationRose E Wang, Michael Everett, Jonathan P. HowICML Workshop: Reinforcement Learning for Real Life 2019 |
 | Certified Adversarial Robustness for Deep Reinforcement LearningBjörn Lütjens, Michael Everett, Jonathan P. HowConference on Robot Learning (CoRL) 2019Paper |
 | Planning Beyond The Sensing Horizon Using a Learned ContextMichael Everett, Justin Miller, Jonathan P. HowIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019Paper |
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 | Multi-Agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement LearningSamaneh Hosseini Semnani, Hugh Liu, Michael Everett, Anton de Ruiter, Jonathan P HowIEEE Robotics and Automation Letters (RA-L) 2020Paper |
 | Efficient Reachability Analysis for Closed-Loop Systems with Neural Network ControllersMichael Everett, Golnaz Habibi, Jonathan P. HowIEEE International Conference on Robotics and Automation (ICRA) 2021Paper |
 | Where to go next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic EnvironmentsBruno Brito, Michael Everett, Jonathan P. How, Javier Alonso-MoraIEEE Robotics and Automation Letters (RA-L) 2021Paper |
 | Neural Network Verification in Control (Tutorial)Michael EverettIEEE Conference on Decision and Control (CDC) 2021Paper |
 | Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement LearningMichael Everett, Yu Fan Chen, Jonathan P. HowIEEE Access: Special Section on Real-Time Machine Learning Applications in Mobile Robotics 2021Paper |
 | Reachability Analysis of Neural Feedback LoopsMichael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. HowIEEE Access 2021Paper |
 | Robustness Analysis of Neural Networks via Efficient Partitioning with Applications in Control SystemsMichael Everett, Golnaz Habibi, Jonathan P. HowIEEE Control Systems Letters (L-CSS) 2021Paper |
 | FASTER: Fast and Safe Trajectory Planner for Flights in Unknown EnvironmentsJesus Tordesillas, Brett T. Lopez, Michael Everett, Jonathan P. HowIEEE Transactions on Robotics (TRO) 2022Paper |
 | Influencing Long-Term Behavior in Multiagent Reinforcement LearningDong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. HowConference on Neural Information Processing Systems (NeurIPS) 2022Paper |
 | Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube-MPCAndrea Tagliabue, Dong-Ki Kim, Michael Everett, Jonathan P. HowIEEE International Conference on Robotics and Automation (ICRA) 2022Paper |
 | Risk-Aware Off-Road Navigation via a Learned Speed Distribution MapXiaoyi Cai, Michael Everett, Jonathan Fink, Jonathan P. HowIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022Paper |
 | Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement LearningMichael Everett*, Björn Lütjens*, Jonathan P. HowIEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2022Paper |
 | Backward Reachability Analysis of Neural Feedback LoopsNicholas Rober, Michael Everett, Jonathan P. HowIEEE Conference on Decision and Control (CDC) 2022Paper |
 | Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road EnvironmentsXiaoyi Cai, Michael Everett, Lakshay Sharma, Philip R. Osteen, Jonathan P. HowIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023Paper |
 | DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback LoopsMichael Everett, Rudy Bunel, Shayegan OmidshafieiIEEE Control Systems Letters (L-CSS) 2023Paper |
 | Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear SystemsNicholas Rober, Sydney M. Katz, Chelsea Sidrane, Esen Yel, Michael Everett, Mykel J. Kochenderfer, Jonathan P. HowIEEE Open Journal of Control Systems (OJ-CSYS): Special Section: Formal Verification and Synthesis of Cyber-Physical Systems 2023Paper |
 | A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback LoopsNicholas Rober, Michael Everett, Songan Zhang, Jonathan P. HowAmerican Controls Conference (ACC) 2023Paper |
 | RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot NavigationLakshay Sharma, Michael Everett, Donggun Lee, Xiaoyi Cai, Philip Osteen, Jonathan P. HowIEEE International Conference on Robotics and Automation (ICRA) 2023Paper |
 | EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road AutonomyXiaoyi Cai, Siddharth Ancha, Lakshay Sharma, Philip R. Osteen, Bernadette Bucher, Stephen Phillips, Jiuguang Wang, Michael Everett, Nicholas Roy, Jonathan P. HowIEEE Transactions on Robotics (TRO) 2024Paper |
 | Collision Avoidance Verification of Multiagent Systems with Learned PoliciesZihao Dong, Shayegan Omidshafiei, Michael EverettIEEE Control Systems Letters (L-CSS) 2024Paper |
 | LiDAR Inertial Odometry And Mapping Using Learned Registration-Relevant FeaturesZihao Dong, Jeff Pflueger, Leonard Jung, David Thorne, Philip R. Osteen, Christa S. Robison, Brett T. Lopez, Michael EverettIEEE International Conference on Robotics and Automation (ICRA) 2024 (accepted)Paper |
 | Chance-Constrained Convex MPC for Robust Quadruped Locomotion Under Parametric and Additive UncertaintiesAnanya Trivedi, Sarvesh Prajapati, Mark Zolotas, Michael Everett, Taskin PadirIEEE Robotics and Automation Letters (RA-L) 2024 (in review)Paper |
| Learning Verifiable Control Policies Using Relaxed VerificationPuja Chaudhury, Alexander Estornell, Michael EverettIEEE Conference on Decision and Control (CDC) 2025 (in review) |
| A Hybrid Framework for Efficient Koopman Operator LearningAlexander Estornell*, Leonard Jung*, Alenna Spiro*, Mario Sznaier, Michael EverettIEEE Conference on Decision and Control (CDC) 2025 (in review) |
 | Principles and Guidelines for Evaluating Social Robot Navigation AlgorithmsAnthony 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-MartinACM Transactions on Human-Robot Interaction (T-HRI) 2025Paper |
 | Continuous Contingency Planning with MPPI within MPPILeonard Jung, Alexander Estornell, Michael EverettLearning for Dynamics and Control Conference (L4DC) 2025 (accepted)Paper |
| Adversarial Decoy Placement for Strategic State Perturbations in Artificial Intelligence Driven DefenseArmita Kazeminajafabadi, Michael Everett, Tian Lan, Nathaniel D. Bastian, Mahdi ImaniIEEE Conference on Decision and Control (CDC) 2025 (in review) |
 | Robust Survival Analysis with Adversarial RegularizationMichael Potter, Stefano Maxenti, Michael EverettIEEE International Conference on Healthcare Informatics (ICHI) 2025 (accepted)Paper |
 | Continuously Optimizing Radar Placement with Model Predictive Path IntegralsMichael Potter, Shuo Tang, Paul Ghanem, Milica Stojanovic, Pau Closas, Murat Akcakaya, Ben Wright, Marius Necsoiu, Deniz Erdogmus, Michael Everett, Tales ImbiribaIEEE Transactions on Aerospace and Electronic Systems (T-AES) 2025Paper |
| Active Learning For Repairable Hardware Systems With Partial CoverageMichael Potter, Beyza Kalkanlı, Deniz Erdoğmuş, Michael Everett2025 (in review)Paper |
| Temporal Point Process Modeling of Aggressive Behavior Onset in Psychiatric Inpatient Youths with AutismMichael Potter, Michael Everett, Ashutosh Singh, Georgios Stratis, Yuna Watanabe, Ahmet Demirkaya, Deniz Erdogmus, Tales Imbiriba, Matthew S Goodwin2025 (in review)Paper |
| Real-Time Adaptive Motion Planning via Point Cloud-Guided, Energy-Based Diffusion and Potential FieldsWondmgezahu Teshome, Kian Behzad, Octavia Camps, Michael Everett, Milad Siami, Mario Sznaier2025 (in review) |