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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
- 2020
[j66]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)- [j65]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) - [j64]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) - [j63]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) - [j62]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) - [j61]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) - [c156]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 - [c155]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 - [c154]Golnaz Habibi, Nikita Jaipuria, Jonathan P. How:
SILA: An Incremental Learning Approach for Pedestrian Trajectory Prediction. CVPR Workshops 2020: 4411-4421 - [c153]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 - [c152]Arpan Kusari, Jonathan P. How:
Predicting optimal value functions by interpolating reward functions in scalarized multi-objective reinforcement learning. ICRA 2020: 7484-7490 - [c151]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 - [i75]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) - [i74]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) - [i73]Rose E. Wang, Michael Everett, Jonathan P. How:
R-MADDPG for Partially Observable Environments and Limited Communication. CoRR abs/2002.06684 (2020) - [i72]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) - [i71]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) - [i70]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) - [i69]Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How:
Asynchronous and Parallel Distributed Pose Graph Optimization. CoRR abs/2003.03281 (2020) - [i68]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) - [i67]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) - [i66]Michael Everett, Björn Lütjens, Jonathan P. How:
Certified Adversarial Robustness for Deep Reinforcement Learning. CoRR abs/2004.06496 (2020) - [i65]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Collision Probabilities for Continuous-Time Systems Without Sampling [with Appendices]. CoRR abs/2006.01109 (2020) - [i64]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
Set-Invariant Constrained Reinforcement Learning with a Meta-Optimizer. CoRR abs/2006.11419 (2020) - [i63]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) - [i62]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)
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) - [c150]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 - [c149]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 - [c148]Brett Thomas Lopez, Jonathan P. How, Jean-Jacques E. Slotine:
Dynamic Tube MPC for Nonlinear Systems. ACC 2019: 1655-1662 - [c147]Björn Lütjens, Michael Everett, Jonathan P. How:
Certified Adversarial Robustness for Deep Reinforcement Learning. CoRL 2019: 1328-1337 - [c146]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 - [c145]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 - [c144]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Efficient Constellation-Based Map-Merging for Semantic SLAM. ICRA 2019: 1302-1308 - [c143]Macheng Shen, Jonathan P. How:
Active Perception in Adversarial Scenarios using Maximum Entropy Deep Reinforcement Learning. ICRA 2019: 3384-3390 - [c142]Björn Lütjens, Michael Everett, Jonathan P. How:
Safe Reinforcement Learning With Model Uncertainty Estimates. ICRA 2019: 8662-8668 - [c141]Michael Everett, Justin Miller, Jonathan P. How:
Planning Beyond The Sensing Horizon Using a Learned Context. IROS 2019: 1064-1071 - [c140]Jesus Tordesillas, Brett Thomas Lopez, Jonathan P. How:
FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments. IROS 2019: 1934-1940 - [c139]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]Macheng Shen, Jonathan P. How:
Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning in Asymmetric Imperfect-Information Games. CoRR abs/1909.08735 (2019) - [i47]Aleix Paris, Brett Thomas Lopez, Jonathan P. How:
Dynamic Landing of an Autonomous Quadrotor on a Moving Platform in Turbulent Wind Conditions. CoRR abs/1909.11071 (2019) - [i46]Michael Everett, Yu Fan Chen, Jonathan P. How:
Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning. CoRR abs/1910.11689 (2019) - [i45]Björn Lütjens, Michael Everett, Jonathan P. How:
Certified Adversarial Robustness for Deep Reinforcement Learning. CoRR abs/1910.12908 (2019) - [i44]Yulun Tian, Kasra Khosoussi, Jonathan P. How:
Block-Coordinate Descent on the Riemannian Staircase for Certifiably Correct Distributed Rotation and Pose Synchronization. CoRR abs/1911.03721 (2019) - [i43]Golnaz Habibi, Nikita Jaipuria, Jonathan P. How:
Incremental Learning of Motion Primitives for Pedestrian Trajectory Prediction at Intersections. CoRR abs/1911.09476 (2019) - 2018
- [j54]Heba Kurdi, Ebtesam Aloboud, Maram Alalwan, Sarah Alhassan, Ebtehal T. Alotaibi, Guillermo Bautista, Jonathan P. How:
Autonomous task allocation for multi-UAV systems based on the locust elastic behavior. Appl. Soft Comput. 71: 110-126 (2018) - [c138]John F. Quindlen, Ufuk Topcu, Girish Chowdhary, Jonathan P. How:
Closed-Loop Statistical Verification of Stochastic Nonlinear Systems Subject to Parametric Uncertainties. ACC 2018: 5460-5466 - [c137]John F. Quindlen, Ufuk Topcu, Girish Chowdhary, Jonathan P. How:
Active Sampling for Closed-Loop Statistical Verification of Uncertain Nonlinear Systems. ACC 2018: 6259-6265 - [c136]Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How:
Crossmodal Attentive Skill Learner. AAMAS 2018: 139-146 - [c135]Brett Thomas Lopez, Jean-Jacques E. Slotine, Jonathan P. How:
Robust Powered Descent with Control Contraction Metrics. CDC 2018: 3483-3490 - [c134]Erin Evans, Stephen Thrasher, Jonathan P. How:
Reference Drag Update Scheme in Shuttle Entry Guidance Using Range Allocator for Tight Constraints. ECC 2018: 362-367 - [c133]Matthew Giamou, Kasra Khosoussi, Jonathan P. How:
Talk Resource-Efficiently to Me: Optimal Communication Planning for Distributed Loop Closure Detection. ICRA 2018: 1-9 - [c132]Brett Thomas Lopez, Jean-Jacques E. Slotine, Jonathan P. How:
Robust Collision Avoidance via Sliding Control. ICRA 2018: 2962-2969 - [c131]Trong Nghia Hoang, Yuchen Xiao, Kavinayan Sivakumar, Christopher Amato, Jonathan P. How:
Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems. ICRA 2018: 6373-6380 - [c130]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Complexity Analysis and Efficient Measurement Selection Primitives for High-Rate Graph SLAM. ICRA 2018: 6505-6512 - [c129]Michael Everett, Yu Fan Chen, Jonathan P. How:
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning. IROS 2018: 3052-3059 - [c128]Macheng Shen, Golnaz Habibi, Jonathan P. How:
Transferable Pedestrian Motion Prediction Models at Intersections. IROS 2018: 4547-4553 - [c127]Yulun Tian, Katherine Liu, Kyel Ok, Loc Tran, Danette Allen, Nicholas Roy, Jonathan P. How:
Search and Rescue Under the Forest Canopy Using Multiple UAS. ISER 2018: 140-152 - [c126]Nikita Jaipuria, Golnaz Habibi, Jonathan P. How:
Learning in the Curbside Coordinate Frame for a Transferable Pedestrian Trajectory Prediction Model. ITSC 2018: 3125-3131 - [c125]Yulun Tian, Kasra Khosoussi, Matthew Giamou, Jonathan P. How, Jonathan Kelly:
Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection. Robotics: Science and Systems 2018 - [c124]Yulun Tian, Kasra Khosoussi, Jonathan P. How:
Resource-Aware Algorithms for Distributed Loop Closure Detection with Provable Performance Guarantees. WAFR 2018: 422-438 - [i42]Macheng Shen, Golnaz Habibi, Jonathan P. How:
Transferable Pedestrian Motion Prediction Models at Intersections. CoRR abs/1804.00495 (2018) - [i41]Michael Everett, Yu Fan Chen, Jonathan P. How:
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning. CoRR abs/1805.01956 (2018) - [i40]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. CoRR abs/1805.07830 (2018) - [i39]Trong Nghia Hoang, Quang Minh Hoang, Kian Hsiang Low, Jonathan P. How:
Collective Online Learning via Decentralized Gaussian Processes in Massive Multi-Agent Systems. CoRR abs/1805.09266 (2018) - [i38]Yulun Tian, Kasra Khosoussi, Matthew Giamou, Jonathan P. How, Jonathan Kelly:
Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection. CoRR abs/1806.00188 (2018) - [i37]Noam Buckman, Han-Lim Choi, Jonathan P. How:
Partial Replanning for Decentralized Dynamic Task Allocation. CoRR abs/1806.04836 (2018) - [i36]Nikita Jaipuria, Golnaz Habibi, Jonathan P. How:
A Transferable Pedestrian Motion Prediction Model for Intersections with Different Geometries. CoRR abs/1806.09444 (2018) - [i35]Golnaz Habibi, Nikita Jaipuria, Jonathan P. How:
Context-Aware Pedestrian Motion Prediction In Urban Intersections. CoRR abs/1806.09453 (2018) - [i34]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Efficient Constellation-Based Map-Merging for Semantic SLAM. CoRR abs/1809.09646 (2018) - [i33]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. CoRR abs/1810.01035 (2018) - [i32]Björn Lütjens, Michael Everett, Jonathan P. How:
Safe Reinforcement Learning with Model Uncertainty Estimates. CoRR abs/1810.08700 (2018) - 2017
- [j53]Shayegan Omidshafiei, Ali-Akbar Agha-Mohammadi, Christopher Amato, Shih-Yuan Liu, Jonathan P. How, John Vian:
Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions. Int. J. Robotics Res. 36(2): 231-258 (2017) - [j52]Luke B. Johnson, Han-Lim Choi, Sameera S. Ponda, Jonathan P. How:
Decentralized Task Allocation Using Local Information Consistency Assumptions. J. Aerosp. Inf. Syst. 14(2): 103-122 (2017) - [j51]Robert C. Grande, Thomas J. Walsh, Girish Chowdhary, Sarah Ferguson, Jonathan P. How:
Online Regression for Data With Changepoints Using Gaussian Processes and Reusable Models. IEEE Trans. Neural Networks Learn. Syst. 28(9): 2115-2128 (2017) - [j50]Beipeng Mu, Liam Paull, Ali-Akbar Agha-Mohammadi, John J. Leonard, Jonathan P. How:
Two-Stage Focused Inference for Resource-Constrained Minimal Collision Navigation. IEEE Trans. Robotics 33(1): 124-140 (2017) - [c123]Taposh Banerjee, Miao Liu, Jonathan P. How:
Quickest change detection approach to optimal control in Markov decision processes with model changes. ACC 2017: 399-405 - [c122]Julian Straub, Trevor Campbell, Jonathan P. How, John W. Fisher III:
Efficient Global Point Cloud Alignment Using Bayesian Nonparametric Mixtures. CVPR 2017: 2403-2412 - [c121]Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian:
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. ICML 2017: 2681-2690 - [c120]Yu Fan Chen, Miao Liu, Michael Everett, Jonathan P. How:
Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning. ICRA 2017: 285-292 - [c119]Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian:
Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. ICRA 2017: 863-870 - [c118]Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian:
Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. ICRA 2017: 871-878 - [c117]Justin Miller, Jonathan P. How:
Predictive positioning and quality of service ridesharing for campus mobility on demand systems. ICRA 2017: 1402-1408 - [c116]Liam Paull, Jacopo Tani, Heejin Ahn, Javier Alonso-Mora, Luca Carlone, Michal Cáp, Yu Fan Chen, Changhyun Choi, Jeff Dusek, Yajun Fang, Daniel Hoehener, Shih-Yuan Liu, Michael Novitzky, Igor Franzoni Okuyama, Jason Pazis, Guy Rosman, Valerio Varricchio, Hsueh-Cheng Wang, Dmitry S. Yershov, Hang Zhao, Michael Benjamin, Christopher Carr, Maria T. Zuber, Sertac Karaman, Emilio Frazzoli, Domitilla Del Vecchio, Daniela Rus, Jonathan P. How, John J. Leonard, Andrea Censi:
Duckietown: An open, inexpensive and flexible platform for autonomy education and research. ICRA 2017: 1497-1504 - [c115]Brett Thomas Lopez, Jonathan P. How:
Aggressive 3-D collision avoidance for high-speed navigation. ICRA 2017: 5759-5765 - [c114]Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How:
Socially aware motion planning with deep reinforcement learning. IROS 2017: 1343-1350 - [c113]Brett Thomas Lopez, Jonathan P. How:
Aggressive collision avoidance with limited field-of-view sensing. IROS 2017: 1358-1365 - [c112]Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How:
Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions. IROS 2017: 1853-1860 - [c111]Matthew Giamou, Yaroslav Babich, Golnaz Habibi, Jonathan P. How:
Stable laser interest point selection for place recognition in a forest. IROS 2017: 4290-4297 - [c110]Justin Miller, Jonathan P. How:
Demand estimation and chance-constrained fleet management for ride hailing. IROS 2017: 4481-4488 - [c109]Jonathan P. How:
Planning and Learning under Uncertainty: Theory and Practice. KDD 2017: 19 - [i31]Justin Miller, Jonathan P. How:
Demand Estimation and Chance-Constrained Fleet Management for Ride Hailing. CoRR abs/1703.02130 (2017) - [i30]Justin Miller, Andres Hasfura, Shih-Yuan Liu, Jonathan P. How:
Dynamic Arrival Rate Estimation for Campus Mobility on Demand Network Graphs. CoRR abs/1703.02145 (2017) - [i29]Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian:
Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations. CoRR abs/1703.05623 (2017) - [i28]Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian:
Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces. CoRR abs/1703.05626 (2017) - [i27]Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian:
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. CoRR abs/1703.06182 (2017) - [i26]Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How:
Socially Aware Motion Planning with Deep Reinforcement Learning. CoRR abs/1703.08862 (2017) - [i25]Beipeng Mu, Shih-Yuan Liu, Liam Paull, John J. Leonard, Jonathan P. How:
SLAM with Objects using a Nonparametric Pose Graph. CoRR abs/1704.05959 (2017) - [i24]John F. Quindlen, Ufuk Topcu, Girish Chowdhary, Jonathan P. How:
Active Sampling for Constrained Simulation-based Verification of Uncertain Nonlinear Systems. CoRR abs/1705.01471 (2017) - [i23]John F. Quindlen, Ufuk Topcu, Girish Chowdhary, Jonathan P. How:
Active Sampling-based Binary Verification of Dynamical Systems. CoRR abs/1706.04268 (2017) - [i22]Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How:
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions. CoRR abs/1707.07399 (2017) - [i21]John F. Quindlen, Ufuk Topcu, Girish Chowdhary, Jonathan P. How:
Closed-Loop Statistical Verification of Stochastic Nonlinear Systems Subject to Parametric Uncertainties. CoRR abs/1709.06645 (2017) - [i20]Matthew Giamou, Kasra Khosoussi, Jonathan P. How:
Talk Resource-Efficiently to Me: Optimal Communication Planning for Distributed SLAM Front-Ends. CoRR abs/1709.06675 (2017) - [i19]Kristoffer M. Frey, Ted J. Steiner, Jonathan P. How:
Complexity Analysis and Efficient Measurement Selection Primitives for High-Rate Graph SLAM. CoRR abs/1709.06821 (2017) - [i18]Trong Nghia Hoang, Yuchen Xiao, Kavinayan Sivakumar, Christopher Amato, Jonathan P. How:
Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems. CoRR abs/1710.06525 (2017) - [i17]