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Jonathan P. How

Massachusetts Institute of Technology

NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows


May 11, 2021
Qiangqiang Huang, Can Pu, Dehann Fourie, Kasra Khosoussi, Jonathan P. How, John J. Leonard

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* 8 pages, 6 figures, to be published in IEEE International Conference on Robotics and Automation (ICRA) 2021 
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Multi-Robot Distributed Semantic Mapping in Unfamiliar Environments through Online Matching of Learned Representations


Mar 27, 2021
Stewart Jamieson, Kaveh Fathian, Kasra Khosoussi, Jonathan P. How, Yogesh Girdhar

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* 7 pages, 6 figures, 1 table; accepted for presentation in IEEE Int. Conf. on Robotics and Automation, ICRA '21, Xi'an, China, June 2021 
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PANTHER: Perception-Aware Trajectory Planner in Dynamic Environments


Mar 10, 2021
Jesus Tordesillas, Jonathan P. How

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* 8 pages 
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Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians


Feb 26, 2021
Bruno Brito, Michael Everett, Jonathan P. How, Javier Alonso-Mora

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* 8 pages, 6 figures 
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LION: Lidar-Inertial Observability-Aware Navigator for Vision-Denied Environments


Feb 05, 2021
Andrea Tagliabue, Jesus Tordesillas, Xiaoyi Cai, Angel Santamaria-Navarro, Jonathan P. How, Luca Carlone, Ali-akbar Agha-mohammadi

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* 2020 International Symposium on Experimental Robotics (ISER 2020) 
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Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams


Jan 26, 2021
Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi, Nikolay Atanasov, George J. Pappas, Jonathan P. How

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* Submitted to ICRA'21 
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Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers


Jan 05, 2021
Michael Everett, Golnaz Habibi, Jonathan P. How

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CLIPPER: A Graph-Theoretic Framework for Robust Data Association


Nov 20, 2020
Parker C. Lusk, Kaveh Fathian, Jonathan P. How

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Kimera-Multi: a System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping


Nov 08, 2020
Yun Chang, Yulun Tian, Jonathan P. How, Luca Carlone

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* 9 pages 
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A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning


Oct 31, 2020
Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How

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* Under review as a conference paper 
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MADER: Trajectory Planner in Multi-Agent and Dynamic Environments


Oct 21, 2020
Jesus Tordesillas, Jonathan P. How

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* 14 pages, 15 figures 
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MINVO Basis: Finding Simplexes with Minimum Volume Enclosing Polynomial Curves


Oct 21, 2020
Jesus Tordesillas, Jonathan P. How

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* 17 pages, 16 figures 
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Robustness Analysis of Neural Networks via Efficient Partitioning: Theory and Applications in Control Systems


Oct 01, 2020
Michael Everett, Golnaz Habibi, Jonathan P. How

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Lunar Terrain Relative Navigation Using a Convolutional Neural Network for Visual Crater Detection


Jul 15, 2020
Lena M. Downes, Ted J. Steiner, Jonathan P. How

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* 6 pages, 4 figures. This work was accepted by the 2020 American Control Conference 
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Set-Invariant Constrained Reinforcement Learning with a Meta-Optimizer


Jul 09, 2020
Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How

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* Accepted to ICML 2020 Workshop Theoretical Foundations of RL 
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Collision Probabilities for Continuous-Time Systems Without Sampling [with Appendices]


Jun 01, 2020
Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How

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* To appear at RSS 2020 
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Certified Adversarial Robustness for Deep Reinforcement Learning


Apr 11, 2020
Michael Everett, Bjorn Lutjens, Jonathan P. How

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* arXiv admin note: text overlap with arXiv:1910.12908 
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Active Reward Learning for Co-Robotic Vision Based Exploration in Bandwidth Limited Environments


Mar 10, 2020
Stewart Jamieson, Jonathan P. How, Yogesh Girdhar

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* 7 pages, 4 figures; accepted for presentation in IEEE Int. Conf. on Robotics and Automation, ICRA '20, Paris, France, June 2020 
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Asynchronous and Parallel Distributed Pose Graph Optimization


Mar 06, 2020
Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How

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Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor


Mar 04, 2020
Andrea Tagliabue, Aleix Paris, Suhan Kim, Regan Kubicek, Sarah Bergbreiter, Jonathan P. How

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* The first two authors contributed equally 
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A Distributed Pipeline for Scalable, Deconflicted Formation Flying


Mar 04, 2020
Parker C. Lusk, Xiaoyi Cai, Samir Wadhwania, Aleix Paris, Kaveh Fathian, Jonathan P. How

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* 8 pages, 8 figures, submitted to 2020 IEEE IROS with IEEE RAS RA-L option 
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Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph


Mar 03, 2020
Chuangchuang Sun, Macheng Shen, Jonathan P. How

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R-MADDPG for Partially Observable Environments and Limited Communication


Feb 18, 2020
Rose E. Wang, Michael Everett, Jonathan P. How

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* Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019 
 * Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019 
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Multi-agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning


Jan 18, 2020
Samaneh Hosseini Semnani, Hugh Liu, Michael Everett, Anton de Ruiter, Jonathan P. How

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


Jan 09, 2020
Jesus Tordesillas, Brett T. Lopez, Michael Everett, Jonathan P. How

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* Journal paper. arXiv admin note: text overlap with arXiv:1903.03558 
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Block-Coordinate Descent on the Riemannian Staircase for Certifiably Correct Distributed Rotation and Pose Synchronization


Dec 21, 2019
Yulun Tian, Kasra Khosoussi, Jonathan P. How

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* technical report version 3 (add missing step in algorithm 1) 
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Incremental Learning of Motion Primitives for Pedestrian Trajectory Prediction at Intersections


Nov 21, 2019
Golnaz Habibi, Nikita Japuria, Jonathan P. How

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