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ORCIDJonathan P. How
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- affiliation: Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
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2020 – today
- 2022
[j80]Sharan Raja, Golnaz Habibi
, Jonathan P. How:
Communication-Aware Consensus-Based Decentralized Task Allocation in Communication Constrained Environments. IEEE Access 10: 19753-19767 (2022)- [j79]Jesus Tordesillas, Jonathan P. How:
PANTHER: Perception-Aware Trajectory Planner in Dynamic Environments. IEEE Access 10: 22662-22677 (2022) - [j78]Jesus Tordesillas, Jonathan P. How:
MADER: Trajectory Planner in Multiagent and Dynamic Environments. IEEE Trans. Robotics 38(1): 463-476 (2022) - [j77]Jesus Tordesillas, Brett Thomas Lopez, Michael Everett, Jonathan P. How:
FASTER: Fast and Safe Trajectory Planner for Navigation in Unknown Environments. IEEE Trans. Robotics 38(2): 922-938 (2022) - [i105]Yulun Tian, Amrit Singh Bedi, Alec Koppel, Miguel Calvo-Fullana, David M. Rosen, Jonathan P. How:
Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation. CoRR abs/2203.00851 (2022) - [i104]Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How:
Influencing Long-Term Behavior in Multiagent Reinforcement Learning. CoRR abs/2203.03535 (2022) - [i103]Lena M. Downes, Dong-Ki Kim, Ted J. Steiner, Jonathan P. How:
City-wide Street-to-Satellite Image Geolocalization of a Mobile Ground Agent. CoRR abs/2203.05612 (2022) - [i102]Macheng Shen, Jonathan P. How:
Safe adaptation in multiagent competition. CoRR abs/2203.07562 (2022) - [i101]Andrew Fishberg, Jonathan P. How:
Multi-Agent Relative Pose Estimation with UWB and Constrained Communications. CoRR abs/2203.11004 (2022) - [i100]Xiaoyi Cai, Michael Everett, Jonathan Fink, Jonathan P. How:
Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map. CoRR abs/2203.13429 (2022) - [i99]Miguel Calvo-Fullana, Jonathan P. How:
Distributed Filtering with Value of Information Censoring. CoRR abs/2204.00474 (2022) - [i98]Nicholas Rober, Michael Everett, Jonathan P. How:
Backward Reachability Analysis for Neural Feedback Loops. CoRR abs/2204.08319 (2022) - [i97]Parker C. Lusk, Jonathan P. How:
Global Data Association for SLAM with 3D Grassmannian Manifold Objects. CoRR abs/2205.08556 (2022) - 2021
- [j76]Michael Everett, Yu Fan Chen, Jonathan P. How:
Collision Avoidance in Pedestrian-Rich Environments With Deep Reinforcement Learning. IEEE Access 9: 10357-10377 (2021) - [j75]Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How:
Reachability Analysis of Neural Feedback Loops. IEEE Access 9: 163938-163953 (2021) - [j74]Brett Thomas Lopez, Jean-Jacques E. Slotine, Jonathan P. How:
Robust Adaptive Control Barrier Functions: An Adaptive and Data-Driven Approach to Safety. IEEE Control. Syst. Lett. 5(3): 1031-1036 (2021) - [j73]Michael Everett, Golnaz Habibi, Jonathan P. How:
Robustness Analysis of Neural Networks via Efficient Partitioning With Applications in Control Systems. IEEE Control. Syst. Lett. 5(6): 2114-2119 (2021) - [j72]Yulun Tian, Kasra Khosoussi, Jonathan P. How:
A resource-aware approach to collaborative loop-closure detection with provable performance guarantees. Int. J. Robotics Res. 40(10-11) (2021) - [j71]Golnaz Habibi, Jonathan P. How:
Human Trajectory Prediction Using Similarity-Based Multi-Model Fusion. IEEE Robotics Autom. Lett. 6(2): 715-722 (2021) - [j70]Bruno Brito, Michael Everett, Jonathan P. How, Javier Alonso-Mora:
Where to go Next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic Environments. IEEE Robotics Autom. Lett. 6(3): 4616-4623 (2021) - [j69]Yulun Tian, Kasra Khosoussi, David M. Rosen, Jonathan P. How:
Distributed Certifiably Correct Pose-Graph Optimization. IEEE Trans. Robotics 37(6): 2137-2156 (2021) - [c193]Macheng Shen, Jonathan P. How:
Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning. ICAPS 2021: 578-587 - [c192]Michael Everett, Golnaz Habibi, Jonathan P. How:
Robustness Analysis of Neural Networks via Efficient Partitioning with Applications in Control Systems. ACC 2021: 888-893 - [c191]Max L. Greene, Zachary I. Bell, Scott A. Nivison, Jonathan P. How, Warren E. Dixon:
Cooperative Model-Based Reinforcement Learning for Approximate Optimal Tracking. ACC 2021: 1973-1978 - [c190]Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How:
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. ICML 2021: 5541-5550 - [c189]Qiangqiang Huang, Can Pu, Dehann Fourie, Kasra Khosoussi, Jonathan P. How, John J. Leonard:
NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows. ICRA 2021: 1095-1102 - [c188]Michael Everett, Golnaz Habibi, Jonathan P. How:
Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers. ICRA 2021: 4384-4390 - [c187]Andrea Tagliabue, Jonathan P. How:
Airflow-Inertial Odometry for Resilient State Estimation on Multirotors. ICRA 2021: 5736-5743 - [c186]Stewart Jamieson, Kaveh Fathian, Kasra Khosoussi, Jonathan P. How, Yogesh A. Girdhar:
Multi-Robot Distributed Semantic Mapping in Unfamiliar Environments through Online Matching of Learned Representations. ICRA 2021: 8587-8593 - [c185]Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi, Nikolay Atanasov, George J. Pappas, Jonathan P. How:
Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams. ICRA 2021: 8859-8865 - [c184]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
FISAR: Forward Invariant Safe Reinforcement Learning with a Deep Neural Network-Based Optimizer. ICRA 2021: 10617-10624 - [c183]Yun Chang, Yulun Tian, Jonathan P. How, Luca Carlone:
Kimera-Multi: a System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping. ICRA 2021: 11210-11218 - [c182]Parker C. Lusk, Kaveh Fathian, Jonathan P. How:
CLIPPER: A Graph-Theoretic Framework for Robust Data Association. ICRA 2021: 13828-13834 - [i96]Michael Everett, Golnaz Habibi, Jonathan P. How:
Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers. CoRR abs/2101.01815 (2021) - [i95]Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi, Nikolay Atanasov, George J. Pappas, Jonathan P. How:
Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams. CoRR abs/2101.11093 (2021) - [i94]Andrea Tagliabue, Jesus Tordesillas, Xiaoyi Cai, Angel Santamaria-Navarro, Jonathan P. How, Luca Carlone, Ali-akbar Agha-mohammadi:
LION: Lidar-Inertial Observability-Aware Navigator for Vision-Denied Environments. CoRR abs/2102.03443 (2021) - [i93]Bruno Brito, Michael Everett, Jonathan P. How, Javier Alonso-Mora:
Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians. CoRR abs/2102.13073 (2021) - [i92]Jesus Tordesillas, Jonathan P. How:
PANTHER: Perception-Aware Trajectory Planner in Dynamic Environments. CoRR abs/2103.06372 (2021) - [i91]Stewart Jamieson, Kaveh Fathian, Kasra Khosoussi, Jonathan P. How, Yogesh A. Girdhar:
Multi-Robot Distributed Semantic Mapping in Unfamiliar Environments through Online Matching of Learned Representations. CoRR abs/2103.14805 (2021) - [i90]Qiangqiang Huang, Can Pu, Dehann Fourie, Kasra Khosoussi, Jonathan P. How, John J. Leonard:
NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows. CoRR abs/2105.05045 (2021) - [i89]Andrea Tagliabue, Jonathan P. How:
Airflow-Inertial Odometry for Resilient State Estimation on Multirotors. CoRR abs/2105.13506 (2021) - [i88]Yulun Tian, Yun Chang, Fernando Herrera Arias, Carlos Nieto-Granda, Jonathan P. How, Luca Carlone:
Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems. CoRR abs/2106.14386 (2021) - [i87]Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How:
Reachability Analysis of Neural Feedback Loops. CoRR abs/2108.04140 (2021) - [i86]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation. CoRR abs/2109.06795 (2021) - [i85]Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro, Jonathan P. How:
Context-Specific Representation Abstraction for Deep Option Learning. CoRR abs/2109.09876 (2021) - [i84]Andrea Tagliabue, Dong-Ki Kim, Michael Everett, Jonathan P. How:
Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC. CoRR abs/2109.09910 (2021) - [i83]Qiangqiang Huang, Can Pu, Kasra Khosoussi, David M. Rosen, Dehann Fourie, Jonathan P. How, John J. Leonard:
Online Incremental Non-Gaussian Inference for SLAM Using Normalizing Flows. CoRR abs/2110.00876 (2021) - [i82]Parker C. Lusk, Ronak Roy, Kaveh Fathian, Jonathan P. How:
MIXER: A Principled Framework for Multimodal, Multiway Data Association. CoRR abs/2111.14990 (2021) - 2020
- [j68]Dong-Ki Kim, Shayegan Omidshafiei, Jason Pazis, Jonathan P. How:
Crossmodal attentive skill learner: learning in Atari and beyond with audio-video inputs. Auton. Agents Multi Agent Syst. 34(1): 16 (2020) - [j67]Adrian Carrio, Jesus Tordesillas, Sai Vemprala, Srikanth Saripalli, Pascual Campoy, Jonathan P. How:
Onboard Detection and Localization of Drones Using Depth Maps. IEEE Access 8: 30480-30490 (2020) - [j66]Hriday Bavle, Paloma de la Puente, Jonathan P. How, Pascual Campoy:
VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems. IEEE Access 8: 60704-60718 (2020) - [j65]Yulun Tian, Katherine Liu, Kyel Ok, Loc Tran, Danette Allen, Nicholas Roy, Jonathan P. How:
Search and rescue under the forest canopy using multiple UAVs. Int. J. Robotics Res. 39(10-11) (2020) - [j64]Samaneh Hosseini Semnani, Hugh Liu, Michael Everett, Anton H. J. de Ruiter, Jonathan P. How:
Multi-Agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning. IEEE Robotics Autom. Lett. 5(2): 3221-3226 (2020) - [j63]Parker C. Lusk, Xiaoyi Cai, Samir Wadhwania, Aleix Paris, Kaveh Fathian, Jonathan P. How:
A Distributed Pipeline for Scalable, Deconflicted Formation Flying. IEEE Robotics Autom. Lett. 5(4): 5213-5220 (2020) - [j62]Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How:
Asynchronous and Parallel Distributed Pose Graph Optimization. IEEE Robotics Autom. Lett. 5(4): 5819-5826 (2020) - [j61]Kaveh Fathian, Kasra Khosoussi, Yulun Tian, Parker C. Lusk, Jonathan P. How:
CLEAR: A Consistent Lifting, Embedding, and Alignment Rectification Algorithm for Multiview Data Association. IEEE Trans. Robotics 36(6): 1686-1703 (2020) - [c181]Lena M. Downes, Ted J. Steiner, Jonathan P. How:
Lunar Terrain Relative Navigation Using a Convolutional Neural Network for Visual Crater Detection. ACC 2020: 4448-4453 - [c180]Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How:
Learning Hierarchical Teaching Policies for Cooperative Agents. AAMAS 2020: 620-628 - [c179]Golnaz Habibi, Nikita Jaipuria, Jonathan P. How:
SILA: An Incremental Learning Approach for Pedestrian Trajectory Prediction. CVPR Workshops 2020: 4411-4421 - [c178]Stewart Jamieson, Jonathan P. How, Yogesh A. Girdhar:
Active Reward Learning for Co-Robotic Vision Based Exploration in Bandwidth Limited Environments. ICRA 2020: 1806-1812 - [c177]Arpan Kusari, Jonathan P. How:
Predicting optimal value functions by interpolating reward functions in scalarized multi-objective reinforcement learning. ICRA 2020: 7484-7490 - [c176]Aleix Paris, Brett Thomas Lopez, Jonathan P. How:
Dynamic Landing of an Autonomous Quadrotor on a Moving Platform in Turbulent Wind Conditions. ICRA 2020: 9577-9583 - [c175]Suhan Kim, Regan Kubicek, Aleix Paris, Andrea Tagliabue, Jonathan P. How, Sarah Bergbreiter:
A Whisker-inspired Fin Sensor for Multi-directional Airflow Sensing. IROS 2020: 1330-1337 - [c174]Andrea Tagliabue, Aleix Paris, Suhan Kim, Regan Kubicek, Sarah Bergbreiter, Jonathan P. How:
Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor. IROS 2020: 1645-1652 - [c173]Chuangchuang Sun, Macheng Shen, Jonathan P. How:
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph. IROS 2020: 11755-11762 - [c172]Andrea Tagliabue, Jesus Tordesillas, Xiaoyi Cai, Angel Santamaria-Navarro, Jonathan P. How, Luca Carlone, Ali-akbar Agha-mohammadi:
LION: Lidar-Inertial Observability-Aware Navigator for Vision-Denied Environments. ISER 2020: 380-390 - [c171]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Collision Probabilities for Continuous-Time Systems Without Sampling. Robotics: Science and Systems 2020 - [i81]Jesus Tordesillas, Brett Thomas Lopez, Michael Everett, Jonathan P. How:
FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments. CoRR abs/2001.04420 (2020) - [i80]Samaneh Hosseini Semnani, Hugh Liu, Michael Everett, Anton H. J. de Ruiter, Jonathan P. How:
Multi-agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning. CoRR abs/2001.06627 (2020) - [i79]Rose E. Wang, Michael Everett, Jonathan P. How:
R-MADDPG for Partially Observable Environments and Limited Communication. CoRR abs/2002.06684 (2020) - [i78]Chuangchuang Sun, Macheng Shen, Jonathan P. How:
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph. CoRR abs/2003.01040 (2020) - [i77]Parker C. Lusk, Xiaoyi Cai, Samir Wadhwania, Aleix Paris, Kaveh Fathian, Jonathan P. How:
A Distributed Pipeline for Scalable, Deconflicted Formation Flying. CoRR abs/2003.01851 (2020) - [i76]Andrea Tagliabue, Aleix Paris, Suhan Kim, Regan Kubicek, Sarah Bergbreiter, Jonathan P. How:
Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor. CoRR abs/2003.02305 (2020) - [i75]Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How:
Asynchronous and Parallel Distributed Pose Graph Optimization. CoRR abs/2003.03281 (2020) - [i74]Stewart Jamieson, Jonathan P. How, Yogesh A. Girdhar:
Active Reward Learning for Co-Robotic Vision Based Exploration in Bandwidth Limited Environments. CoRR abs/2003.05016 (2020) - [i73]Brett Thomas Lopez, Jean-Jacques E. Slotine, Jonathan P. How:
Adaptive Safety for Uncertain Nonlinear Systems with Control Barrier Functions and Contraction Metrics. CoRR abs/2003.10028 (2020) - [i72]Michael Everett, Björn Lütjens, Jonathan P. How:
Certified Adversarial Robustness for Deep Reinforcement Learning. CoRR abs/2004.06496 (2020) - [i71]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Collision Probabilities for Continuous-Time Systems Without Sampling [with Appendices]. CoRR abs/2006.01109 (2020) - [i70]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
Set-Invariant Constrained Reinforcement Learning with a Meta-Optimizer. CoRR abs/2006.11419 (2020) - [i69]Lena M. Downes, Ted J. Steiner, Jonathan P. How:
Lunar Terrain Relative Navigation Using a Convolutional Neural Network for Visual Crater Detection. CoRR abs/2007.07702 (2020) - [i68]Michael Everett, Golnaz Habibi, Jonathan P. How:
Robustness Analysis of Neural Networks via Efficient Partitioning: Theory and Applications in Control Systems. CoRR abs/2010.00540 (2020) - [i67]Jesus Tordesillas, Jonathan P. How:
MINVO Basis: Finding Simplexes with Minimum Volume Enclosing Polynomial Curves. CoRR abs/2010.10726 (2020) - [i66]Jesus Tordesillas, Jonathan P. How:
MADER: Trajectory Planner in Multi-Agent and Dynamic Environments. CoRR abs/2010.11061 (2020) - [i65]Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How:
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. CoRR abs/2011.00382 (2020) - [i64]Yun Chang, Yulun Tian, Jonathan P. How, Luca Carlone:
Kimera-Multi: a System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping. CoRR abs/2011.04087 (2020) - [i63]Parker C. Lusk, Kaveh Fathian, Jonathan P. How:
CLIPPER: A Graph-Theoretic Framework for Robust Data Association. CoRR abs/2011.10202 (2020) - [i62]Savva Morozov, Parker C. Lusk, Brett Thomas Lopez, Jonathan P. How:
Performance Analysis of Adaptive Dynamic Tube MPC. CoRR abs/2012.12403 (2020)
2010 – 2019
- 2019
- [j60]Kasra Khosoussi, Matthew Giamou, Gaurav S. Sukhatme, Shoudong Huang, Gamini Dissanayake, Jonathan P. How:
Reliable Graphs for SLAM. Int. J. Robotics Res. 38(2-3) (2019) - [j59]Christopher Amato, George Dimitri Konidaris, Leslie Pack Kaelbling, Jonathan P. How:
Modeling and Planning with Macro-Actions in Decentralized POMDPs. J. Artif. Intell. Res. 64: 817-859 (2019) - [j58]Trevor Campbell, Brian Kulis, Jonathan P. How:
Dynamic Clustering Algorithms via Small-Variance Analysis of Markov Chain Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. 41(6): 1338-1352 (2019) - [j57]Lee E. Clement, Valentin Peretroukhin, Matthew Giamou, John J. Leonard, Hadas Kress-Gazit, Jonathan P. How, Michael Milford, Oliver Brock, Ryan Gariepy, Nicholas Roy, Hallie Siegel, Ludovic Righetti, Aude Billard, Jonathan Kelly:
Where Do We Go From Here? Debates on the Future of Robotics Research at ICRA 2019 [From the Field]. IEEE Robotics Autom. Mag. 26(3): 7-10 (2019) - [j56]Alejandro Rodriguez-Ramos, Adrian Alvarez-Fernandez, Hriday Bavle, Pascual Campoy, Jonathan P. How:
Vision-Based Multirotor Following Using Synthetic Learning Techniques. Sensors 19(21): 4794 (2019) - [j55]Hongchuan Wei, Pingping Zhu, Miao Liu, Jonathan P. How, Silvia Ferrari:
Automatic Pan-Tilt Camera Control for Learning Dirichlet Process Gaussian Process (DPGP) Mixture Models of Multiple Moving Targets. IEEE Trans. Autom. Control. 64(1): 159-173 (2019) - [c170]Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How:
Learning to Teach in Cooperative Multiagent Reinforcement Learning. AAAI 2019: 6128-6136 - [c169]Trong Nghia Hoang, Quang Minh Hoang, Kian Hsiang Low, Jonathan P. How:
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems. AAAI 2019: 7850-7857 - [c168]Brett Thomas Lopez, Jonathan P. How, Jean-Jacques E. Slotine:
Dynamic Tube MPC for Nonlinear Systems. ACC 2019: 1655-1662 - [c167]Björn Lütjens, Michael Everett, Jonathan P. How:
Certified Adversarial Robustness for Deep Reinforcement Learning. CoRL 2019: 1328-1337 - [c166]Kyel Ok, Katherine Liu, Kristoffer M. Frey, Jonathan P. How, Nicholas Roy:
Robust Object-based SLAM for High-speed Autonomous Navigation. ICRA 2019: 669-675 - [c165]Jesus Tordesillas, Brett Thomas Lopez, John Carter, John Ware, Jonathan P. How:
Real-Time Planning with Multi-Fidelity Models for Agile Flights in Unknown Environments. ICRA 2019: 725-731 - [c164]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Efficient Constellation-Based Map-Merging for Semantic SLAM. ICRA 2019: 1302-1308 - [c163]Macheng Shen, Jonathan P. How:
Active Perception in Adversarial Scenarios using Maximum Entropy Deep Reinforcement Learning. ICRA 2019: 3384-3390 - [c162]Björn Lütjens, Michael Everett, Jonathan P. How:
Safe Reinforcement Learning With Model Uncertainty Estimates. ICRA 2019: 8662-8668 - [c161]Michael Everett, Justin Miller, Jonathan P. How:
Planning Beyond The Sensing Horizon Using a Learned Context. IROS 2019: 1064-1071 - [c160]Jesus Tordesillas, Brett Thomas Lopez, Jonathan P. How:
FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments. IROS 2019: 1934-1940 - [c159]Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How:
Policy Distillation and Value Matching in Multiagent Reinforcement Learning. IROS 2019: 8193-8200 - [i61]Yulun Tian, Kasra Khosoussi, Jonathan P. How:
Resource-Aware Algorithms for Distributed Loop Closure Detection with Provable Performance Guarantees. CoRR abs/1901.05925 (2019) - [i60]Kaveh Fathian, Kasra Khosoussi, Parker C. Lusk, Yulun Tian, Jonathan P. How:
CLEAR: A Consistent Lifting, Embedding, and Alignment Rectification Algorithm for Multi-Agent Data Association. CoRR abs/1902.02256 (2019) - [i59]Macheng Shen, Jonathan P. How:
Active Perception in Adversarial Scenarios using Maximum Entropy Deep Reinforcement Learning. CoRR abs/1902.05644 (2019) - [i58]Yulun Tian, Kasra Khosoussi, Jonathan P. How:
Block-Coordinate Minimization for Large SDPs with Block-Diagonal Constraints. CoRR abs/1903.00597 (2019) - [i57]Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How:
Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning. CoRR abs/1903.03216 (2019) - [i56]Jesus Tordesillas, Brett Thomas Lopez, Jonathan P. How:
FaSTraP: Fast and Safe Trajectory Planner for Flights in Unknown Environments. CoRR abs/1903.03558 (2019) - [i55]Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How:
Policy Distillation and Value Matching in Multiagent Reinforcement Learning. CoRR abs/1903.06592 (2019) - [i54]Yulun Tian, Kasra Khosoussi, Jonathan P. How:
A Resource-Aware Approach to Collaborative Loop Closure Detection with Provable Performance Guarantees. CoRR abs/1907.04904 (2019) - [i53]Brett Thomas Lopez, Jean-Jacques E. Slotine, Jonathan P. How:
Dynamic Tube MPC for Nonlinear Systems. CoRR abs/1907.06553 (2019) - [i52]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Towards Online Observability-Aware Trajectory Optimization for Landmark-based Estimators. CoRR abs/1908.03790 (2019) - [i51]Michael Everett, Justin Miller, Jonathan P. How:
Planning Beyond the Sensing Horizon Using a Learned Context. CoRR abs/1908.09171 (2019) - [i50]Yulun Tian, Katherine Liu, Kyel Ok, Loc Tran, Danette Allen, Nicholas Roy, Jonathan P. How:
Search and Rescue under the Forest Canopy using Multiple UAVs. CoRR abs/1908.10541 (2019) - [i49]Arpan Kusari, Jonathan P. How:
Predicting optimal value functions by interpolating reward functions in scalarized multi-objective reinforcement learning. CoRR abs/1909.05004 (2019) - [i48]