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ORCIDGaurav S. Sukhatme
G. Stefano Sukhatme
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- affiliation: University of Southern California, Los Angeles, USA
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2020 – today
- 2022
[j100]Pradipta Ghosh
, Xiaochen Liu, Hang Qiu, Marcos A. M. Vieira, Gaurav S. Sukhatme, Ramesh Govindan:
Sensing the Sensor: Estimating Camera Properties with Minimal Information. ACM Trans. Sens. Networks 18(2): 28:1-28:26 (2022)- [j99]Amanda Prorok, Vijay Kumar, Brian M. Sadler, Gaurav S. Sukhatme:
Introduction to the Special Section on Resilience in Networked Robotic Systems. IEEE Trans. Robotics 38(1): 2-4 (2022) - [j98]Ragesh Kumar Ramachandran, Pietro Pierpaoli, Magnus Egerstedt, Gaurav S. Sukhatme:
Resilient Monitoring in Heterogeneous Multi-Robot Systems Through Network Reconfiguration. IEEE Trans. Robotics 38(1): 126-138 (2022) - [i69]Zhiwei Jia, Kaixiang Lin, Yizhou Zhao, Qiaozi Gao, Govind Thattai, Gaurav S. Sukhatme:
Learning to Act with Affordance-Aware Multimodal Neural SLAM. CoRR abs/2201.09862 (2022) - [i68]Isabel M. Rayas Fernández, Christopher E. Denniston, David A. Caron, Gaurav S. Sukhatme:
Adaptive Sampling to Estimate Quantiles for Guiding Physical Sampling. CoRR abs/2201.10633 (2022) - [i67]Cristian-Paul Bara, Qing Ping, Abhinav Mathur, Govind Thattai, Rohith MV, Gaurav S. Sukhatme:
Privacy Preserving Visual Question Answering. CoRR abs/2202.07712 (2022) - [i66]Aviv Adler, Oscar Mickelin, Ragesh K. Ramachandran, Gaurav S. Sukhatme, Sertac Karaman:
The Role of Heterogeneity in Autonomous Perimeter Defense Problems. CoRR abs/2202.10433 (2022) - [i65]Xiaofeng Gao, Qiaozi Gao, Ran Gong, Kaixiang Lin, Govind Thattai, Gaurav S. Sukhatme:
DialFRED: Dialogue-Enabled Agents for Embodied Instruction Following. CoRR abs/2202.13330 (2022) - [i64]Eric Heiden, Ziang Liu, Vibhav Vineet, Erwin Coumans, Gaurav S. Sukhatme:
Inferring Articulated Rigid Body Dynamics from RGBD Video. CoRR abs/2203.10488 (2022) - 2021
- [j97]Henrik I. Christensen, Nancy M. Amato, Holly A. Yanco, Maja J. Mataric, Howie Choset, Ann W. Drobnis, Ken Goldberg, Jessy W. Grizzle, Gregory D. Hager, John M. Hollerbach, Seth Hutchinson, Venkat Krovi, Daniel Lee, Bill Smart, Jeff Trinkle, Gaurav S. Sukhatme:
A Roadmap for US Robotics - From Internet to Robotics 2020 Edition. Found. Trends Robotics 8(4): 307-424 (2021) - [j96]Eric Heiden, Luigi Palmieri, Leonard Bruns, Kai Oliver Arras, Gaurav S. Sukhatme, Sven Koenig:
Bench-MR: A Motion Planning Benchmark for Wheeled Mobile Robots. IEEE Robotics Autom. Lett. 6(3): 4536-4543 (2021) - [j95]Ragesh Kumar Ramachandran, Nicole Fronda, Gaurav S. Sukhatme:
Resilience in Multirobot Multitarget Tracking With Unknown Number of Targets Through Reconfiguration. IEEE Trans. Control. Netw. Syst. 8(2): 609-620 (2021) - [c275]Sumeet Batra, Zhehui Huang, Aleksei Petrenko, Tushar Kumar, Artem Molchanov, Gaurav S. Sukhatme:
Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning. CoRL 2021: 576-586 - [c274]I-Chun Arthur Liu, Shagun Uppal, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert, Youngwoon Lee:
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation. CoRL 2021: 641-650 - [c273]Gautam Salhotra, Christopher E. Denniston, David A. Caron, Gaurav S. Sukhatme:
Adaptive Sampling using POMDPs with Domain-Specific Considerations. ICRA 2021: 2385-2391 - [c272]Eric Heiden, David Millard, Erwin Coumans, Yizhou Sheng, Gaurav S. Sukhatme:
NeuralSim: Augmenting Differentiable Simulators with Neural Networks. ICRA 2021: 9474-9481 - [c271]James A. Preiss, Gaurav S. Sukhatme:
Suboptimal coverings for continuous spaces of control tasks. L4DC 2021: 547-558 - [c270]Peter Englert, Isabel M. Rayas Fernández, Ragesh Kumar Ramachandran, Gaurav S. Sukhatme:
Sampling-Based Motion Planning on Sequenced Manifolds. Robotics: Science and Systems 2021 - [i63]James A. Preiss, Gaurav S. Sukhatme:
Suboptimal coverings for continuous spaces of control tasks. CoRR abs/2104.11865 (2021) - [i62]Stephanie Kemna, Sara Kangaslahti, Oliver Kroemer, Gaurav S. Sukhatme:
Adaptive Sampling: Algorithmic vs. Human Waypoint Selection. CoRR abs/2104.11962 (2021) - [i61]Siddharth Mayya, Ragesh K. Ramachandran, Lifeng Zhou, Gaurav S. Sukhatme, Vijay Kumar:
Adaptive and Risk-Aware Target Tracking with Heterogeneous Robot Teams. CoRR abs/2105.03813 (2021) - [i60]K. R. Zentner, Ryan Julian, Ujjwal Puri, Yulun Zhang, Gaurav S. Sukhatme:
Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning. CoRR abs/2106.13237 (2021) - [i59]Alessandro Suglia, Qiaozi Gao, Jesse Thomason, Govind Thattai, Gaurav S. Sukhatme:
Embodied BERT: A Transformer Model for Embodied, Language-guided Visual Task Completion. CoRR abs/2108.04927 (2021) - [i58]Sumeet Batra, Zhehui Huang, Aleksei Petrenko, Tushar Kumar, Artem Molchanov, Gaurav S. Sukhatme:
Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning. CoRR abs/2109.07735 (2021) - [i57]Eric Heiden, Christopher E. Denniston, David Millard, Fabio Ramos, Gaurav S. Sukhatme:
Probabilistic Inference of Simulation Parameters via Parallel Differentiable Simulation. CoRR abs/2109.08815 (2021) - [i56]Gautam Salhotra, Christopher E. Denniston, David A. Caron, Gaurav S. Sukhatme:
Adaptive Sampling using POMDPs with Domain-Specific Considerations. CoRR abs/2109.11595 (2021) - [i55]Amanda Prorok, Matthew Malencia, Luca Carlone, Gaurav S. Sukhatme, Brian M. Sadler, Vijay Kumar:
Beyond Robustness: A Taxonomy of Approaches towards Resilient Multi-Robot Systems. CoRR abs/2109.12343 (2021) - [i54]K. R. Zentner, Ryan Julian, Ujjwal Puri, Yulun Zhang, Gaurav S. Sukhatme:
A Simple Approach to Continual Learning by Transferring Skill Parameters. CoRR abs/2110.10255 (2021) - [i53]Nicholas Roy, Ingmar Posner, Tim D. Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Daniel E. Koditschek, Tomás Lozano-Pérez, Vikash Mansinghka, Christopher J. Pal, Blake A. Richards, Dorsa Sadigh, Stefan Schaal, Gaurav S. Sukhatme, Denis Thérien, Marc Toussaint, Michiel van de Panne:
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence. CoRR abs/2110.15245 (2021) - [i52]Yizhou Zhao, Kaixiang Lin, Zhiwei Jia, Qiaozi Gao, Govind Thattai, Jesse Thomason, Gaurav S. Sukhatme:
LUMINOUS: Indoor Scene Generation for Embodied AI Challenges. CoRR abs/2111.05527 (2021) - [i51]I-Chun Arthur Liu, Shagun Uppal, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert, Youngwoon Lee:
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation. CoRR abs/2111.06383 (2021) - 2020
- [j94]Ryan Julian, Eric Heiden, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Scaling simulation-to-real transfer by learning a latent space of robot skills. Int. J. Robotics Res. 39(10-11) (2020) - [c269]Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert:
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments. CoRL 2020: 589-603 - [c268]Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman:
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning. CoRL 2020: 2120-2136 - [c267]Giovanni Sutanto, Isabel M. Rayas Fernández, Peter Englert, Ragesh Kumar Ramachandran, Gaurav S. Sukhatme:
Learning Equality Constraints for Motion Planning on Manifolds. CoRL 2020: 2292-2305 - [c266]Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof, Marcos Augusto M. Vieira, Kevin Chan, Ramesh Govindan, Gaurav S. Sukhatme, Paulo Tabuada, Gunjan Verma:
Rapid Top-Down Synthesis of Large-Scale IoT Networks. ICCCN 2020: 1-9 - [c265]Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav S. Sukhatme, Vladlen Koltun:
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning. ICML 2020: 7652-7662 - [c264]Sarah Bechtle, Artem Molchanov, Yevgen Chebotar, Edward Grefenstette, Ludovic Righetti, Gaurav S. Sukhatme, Franziska Meier:
Meta Learning via Learned Loss. ICPR 2020: 4161-4168 - [c263]Eric Heiden, Ziang Liu, Ragesh K. Ramachandran, Gaurav S. Sukhatme:
Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking. ICRA 2020: 2595-2601 - [c262]Ragesh K. Ramachandran, Nicole Fronda, Gaurav S. Sukhatme:
Resilience in multi-robot target tracking through reconfiguration. ICRA 2020: 4551-4557 - [c261]Pradipta Ghosh, Paulo Tabuada, Ramesh Govindan, Gaurav S. Sukhatme:
Persistent Connected Power Constrained Surveillance with Unmanned Aerial Vehicles. IROS 2020: 1501-1508 - [c260]Elerson Rubens da Silva Santos, Marcos Augusto M. Vieira, Gaurav S. Sukhatme:
Mobile Robot Localization under Non-Gaussian noise using Correntropy Similarity Metric. IROS 2020: 8534-8539 - [c259]Renato Fernando dos Santos, Ragesh K. Ramachandran, Marcos Augusto M. Vieira, Gaurav S. Sukhatme:
Pac-Man is Overkill. IROS 2020: 11652-11657 - [c258]Ragesh K. Ramachandran, Lifeng Zhou, James A. Preiss, Gaurav S. Sukhatme:
Resilient Coverage: Exploring the Local-to-Global Trade-off. IROS 2020: 11740-11747 - [c257]Christopher E. Denniston, Aravind Kumaraguru, David A. Caron, Gaurav S. Sukhatme:
Incorporating Noise into Adaptive Sampling. ISER 2020: 198-208 - [c256]Giovanni Sutanto, Austin S. Wang, Yixin Lin, Mustafa Mukadam, Gaurav S. Sukhatme, Akshara Rai, Franziska Meier:
Encoding Physical Constraints in Differentiable Newton-Euler Algorithm. L4DC 2020: 804-813 - [i50]David Millard, Eric Heiden, Shubham Agrawal, Gaurav S. Sukhatme:
Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics. CoRR abs/2001.08539 (2020) - [i49]Giovanni Sutanto, Austin S. Wang, Yixin Lin, Mustafa Mukadam, Gaurav S. Sukhatme, Akshara Rai, Franziska Meier:
Encoding Physical Constraints in Differentiable Newton-Euler Algorithm. CoRR abs/2001.08861 (2020) - [i48]Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof, Marcos Augusto M. Vieira, Kevin S. Chan, Ramesh Govindan, Gaurav S. Sukhatme, Paulo Tabuada, Gunjan Verma:
Rapid Top-Down Synthesis of Large-Scale IoT Networks. CoRR abs/2002.04244 (2020) - [i47]Eric Heiden, Luigi Palmieri, Kai Oliver Arras, Gaurav S. Sukhatme, Sven Koenig:
Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots. CoRR abs/2003.03543 (2020) - [i46]Pradipta Ghosh, Xiaochen Liu, Hang Qiu, Marcos Augusto M. Vieira, Gaurav S. Sukhatme, Ramesh Govindan:
On Localizing a Camera from a Single Image. CoRR abs/2003.10664 (2020) - [i45]Ragesh K. Ramachandran, Nicole Fronda, Gaurav S. Sukhatme:
Resilience in multi-robot multi-target tracking with unknown number of targets through reconfiguration. CoRR abs/2004.07197 (2020) - [i44]Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman:
Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation. CoRR abs/2004.10190 (2020) - [i43]Max Pflueger, Gaurav S. Sukhatme:
Plan-Space State Embeddings for Improved Reinforcement Learning. CoRR abs/2004.14567 (2020) - [i42]Peter Englert, Isabel M. Rayas Fernández, Ragesh K. Ramachandran, Gaurav S. Sukhatme:
Sampling-Based Motion Planning on Manifold Sequences. CoRR abs/2006.02027 (2020) - [i41]Isabel M. Rayas Fernández, Giovanni Sutanto, Peter Englert, Ragesh K. Ramachandran, Gaurav S. Sukhatme:
Learning Manifolds for Sequential Motion Planning. CoRR abs/2006.07746 (2020) - [i40]Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav S. Sukhatme, Vladlen Koltun:
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning. CoRR abs/2006.11751 (2020) - [i39]Ali-akbar Agha-mohammadi, Eric Heiden, Karol Hausman, Gaurav S. Sukhatme:
Confidence-rich grid mapping. CoRR abs/2006.15754 (2020) - [i38]Giovanni Sutanto, Katharina Rombach, Yevgen Chebotar, Zhe Su, Stefan Schaal, Gaurav S. Sukhatme, Franziska Meier:
Supervised Learning and Reinforcement Learning of Feedback Models for Reactive Behaviors: Tactile Feedback Testbed. CoRR abs/2007.00450 (2020) - [i37]Eric Heiden, David Millard, Erwin Coumans, Gaurav S. Sukhatme:
Augmenting Differentiable Simulators with Neural Networks to Close the Sim2Real Gap. CoRR abs/2007.06045 (2020) - [i36]Ragesh K. Ramachandran, Pietro Pierpaoli, Magnus Egerstedt, Gaurav S. Sukhatme:
Resilient Monitoring in Heterogeneous Multi-robot Systems through Network Reconfiguration. CoRR abs/2008.01321 (2020) - [i35]Giovanni Sutanto, Isabel M. Rayas Fernández, Peter Englert, Ragesh K. Ramachandran, Gaurav S. Sukhatme:
Learning Equality Constraints for Motion Planning on Manifolds. CoRR abs/2009.11852 (2020) - [i34]Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert:
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments. CoRR abs/2010.11940 (2020) - [i33]Eric Heiden, David Millard, Erwin Coumans, Yizhou Sheng, Gaurav S. Sukhatme:
NeuralSim: Augmenting Differentiable Simulators with Neural Networks. CoRR abs/2011.04217 (2020)
2010 – 2019
- 2019
- [j93]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) - [j92]Ali-akbar Agha-mohammadi, Eric Heiden, Karol Hausman, Gaurav S. Sukhatme:
Confidence-rich grid mapping. Int. J. Robotics Res. 38(12-13) (2019) - [j91]Max Pflueger, Ali-Akbar Agha-Mohammadi, Gaurav S. Sukhatme:
Rover-IRL: Inverse Reinforcement Learning With Soft Value Iteration Networks for Planetary Rover Path Planning. IEEE Robotics Autom. Lett. 4(2): 1387-1394 (2019) - [c255]Nicholas Fung, John G. Rogers III, Carlos Nieto, Henrik I. Christensen, Stephanie Kemna, Gaurav S. Sukhatme:
Coordinating multi-robot systems through environment partitioning for adaptive informative sampling. ICRA 2019: 3231-3237 - [c254]Artem Molchanov, Tao Chen, Wolfgang Hönig, James A. Preiss, Nora Ayanian, Gaurav S. Sukhatme:
Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors. IROS 2019: 59-66 - [c253]Alexander S. Koumis, James A. Preiss, Gaurav S. Sukhatme:
Estimating Metric Scale Visual Odometry from Videos using 3D Convolutional Networks. IROS 2019: 265-272 - [c252]Ragesh K. Ramachandran, James A. Preiss, Gaurav S. Sukhatme:
Resilience by Reconfiguration: Exploiting Heterogeneity in Robot Teams. IROS 2019: 6518-6525 - [i32]Shoubhik Debnath, Lantao Liu, Gaurav S. Sukhatme:
Reachability and Differential based Heuristics for Solving Markov Decision Processes. CoRR abs/1901.00921 (2019) - [i31]Shoubhik Debnath, Lantao Liu, Gaurav S. Sukhatme:
Solving Markov Decision Processes with Reachability Characterization from Mean First Passage Times. CoRR abs/1901.01229 (2019) - [i30]Shoubhik Debnath, Gaurav S. Sukhatme, Lantao Liu:
Accelerating Goal-Directed Reinforcement Learning by Model Characterization. CoRR abs/1901.01977 (2019) - [i29]Artem Molchanov, Tao Chen, Wolfgang Hönig, James A. Preiss, Nora Ayanian, Gaurav S. Sukhatme:
Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors. CoRR abs/1903.04628 (2019) - [i28]Ragesh K. Ramachandran, James A. Preiss, Gaurav S. Sukhatme:
Resilience by Reconfiguration: Exploiting Heterogeneity in Robot Teams. CoRR abs/1903.04856 (2019) - [i27]Eric Heiden, David Millard, Hejia Zhang, Gaurav S. Sukhatme:
Interactive Differentiable Simulation. CoRR abs/1905.10706 (2019) - [i26]Yevgen Chebotar, Artem Molchanov, Sarah Bechtle, Ludovic Righetti, Franziska Meier, Gaurav S. Sukhatme:
Meta-Learning via Learned Loss. CoRR abs/1906.05374 (2019) - [i25]Ragesh K. Ramachandran, Nicole Fronda, Gaurav S. Sukhatme:
Resilience in multi-robot target tracking through reconfiguration. CoRR abs/1910.01300 (2019) - [i24]Ragesh K. Ramachandran, Lifeng Zhou, Gaurav S. Sukhatme:
Resilient Coverage: Exploring the Local-to-Global Trade-off. CoRR abs/1910.01917 (2019) - [i23]Eric Heiden, Ziang Liu, Ragesh K. Ramachandran, Gaurav S. Sukhatme:
Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking. CoRR abs/1912.01652 (2019) - 2018
- [j90]Tarek F. Abdelzaher, Nora Ayanian, Tamer Basar, Suhas N. Diggavi, Jana Diesner, Deepak Ganesan, Ramesh Govindan, Susmit Jha, Tancrède Lepoint, Benjamin M. Marlin, Klara Nahrstedt, David M. Nicol, Raj Rajkumar, Stephen Russell, Sanjit A. Seshia, Fei Sha, Prashant J. Shenoy, Mani B. Srivastava, Gaurav S. Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin H. Vaidya, Venugopal V. Veeravalli:
Toward an Internet of Battlefield Things: A Resilience Perspective. Computer 51(11): 24-36 (2018) - [j89]James A. Preiss, Karol Hausman, Gaurav S. Sukhatme, Stephan Weiss:
Simultaneous self-calibration and navigation using trajectory optimization. Int. J. Robotics Res. 37(13-14) (2018) - [j88]Kai-Chieh Ma, Lantao Liu, Hordur Kristinn Heidarsson, Gaurav S. Sukhatme:
Data-driven learning and planning for environmental sampling. J. Field Robotics 35(5): 643-661 (2018) - [j87]Lantao Liu, Gaurav S. Sukhatme:
A Solution to Time-Varying Markov Decision Processes. IEEE Robotics Autom. Lett. 3(3): 1631-1638 (2018) - [j86]Wolfgang Hönig, James A. Preiss, T. K. Satish Kumar, Gaurav S. Sukhatme, Nora Ayanian:
Trajectory Planning for Quadrotor Swarms. IEEE Trans. Robotics 34(4): 856-869 (2018) - [c251]Chen Huang, Lantao Liu, Gaurav S. Sukhatme:
Learning to Act in Partially Structured Dynamic Environment. AAAI Spring Symposia 2018 - [c250]Arnout Devos, Jakob Dhondt, Eugen Stripling, Bart Baesens, Seppe vanden Broucke, Gaurav S. Sukhatme:
Profit Maximizing Logistic Regression Modeling for Credit Scoring. DSW 2018: 125-129 - [c249]Tarek F. Abdelzaher, Nora Ayanian, Tamer Basar, Suhas N. Diggavi, Jana Diesner, Deepak Ganesan, Ramesh Govindan, Susmit Jha, Tancrède Lepoint, Benjamin M. Marlin, Klara Nahrstedt, David M. Nicol, Raj Rajkumar, Stephen Russell, Sanjit A. Seshia, Fei Sha, Prashant J. Shenoy, Mani B. Srivastava, Gaurav S. Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin H. Vaidya, Venugopal V. Veeravalli:
Will Distributed Computing Revolutionize Peace? The Emergence of Battlefield IoT. ICDCS 2018: 1129-1138 - [c248]Eric Heiden, Luigi Palmieri, Sven Koenig, Kai Oliver Arras, Gaurav S. Sukhatme:
Gradient-Informed Path Smoothing for Wheeled Mobile Robots. ICRA 2018: 1710-1717 - [c247]Zhe Su, Oliver Kroemer, Gerald E. Loeb, Gaurav S. Sukhatme, Stefan Schaal:
Learning Manipulation Graphs from Demonstrations Using Multimodal Sensory Signals. ICRA 2018: 2758-2765 - [c246]Stephanie Kemna, Oliver Kroemer, Gaurav S. Sukhatme:
Pilot Surveys for Adaptive Informative Sampling. ICRA 2018: 6417-6424 - [c245]Shoubhik Debnath, Gaurav S. Sukhatme, Lantao Liu:
Accelerating Goal-Directed Reinforcement Learning by Model Characterization. IROS 2018: 1-9 - [c244]Shoubhik Debnath, Lantao Liu, Gaurav S. Sukhatme:
Solving Markov Decision Processes with Reachability Characterization from Mean First Passage Times. IROS 2018: 7063-7070 - [c243]Ryan Julian, Eric Heiden, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Scaling Simulation-to-Real Transfer by Learning Composable Robot Skills. ISER 2018: 267-279 - [c242]Carlos Nieto-Granda, John G. Rogers III, Nicholas Fung, Stephanie Kemna, Henrik I. Christensen, Gaurav S. Sukhatme:
On-Line Coordination Tasks for Multi-robot Systems Using Adaptive Informative Sampling. ISER 2018: 318-327 - [i22]Chris Denniston, Thomas R. Krogstad, Stephanie Kemna, Gaurav S. Sukhatme:
Planning Safe Paths through Hazardous Environments. CoRR abs/1803.00664 (2018) - [i21]Artem Molchanov, Karol Hausman, Stan Birchfield, Gaurav S. Sukhatme:
Region Growing Curriculum Generation for Reinforcement Learning. CoRR abs/1807.01425 (2018) - [i20]Ryan Julian, Eric Heiden, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Scaling simulation-to-real transfer by learning composable robot skills. CoRR abs/1809.10253 (2018) - [i19]Hejia Zhang, Eric Heiden, Ryan Julian, Zhangpeng He, Joseph J. Lim, Gaurav S. Sukhatme:
Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation. CoRR abs/1810.00146 (2018) - [i18]Zhanpeng He, Ryan Julian, Eric Heiden, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations. CoRR abs/1810.02422 (2018) - 2017
- [j85]Karol Hausman, James A. Preiss, Gaurav S. Sukhatme, Stephan Weiss:
Observability-Aware Trajectory Optimization for Self-Calibration With Application to UAVs. IEEE Robotics Autom. Lett. 2(3): 1770-1777 (2017) - [j84]Ryan K. Williams, Andrea Gasparri, Giovanni Ulivi, Gaurav S. Sukhatme:
Generalized Topology Control for Nonholonomic Teams With Discontinuous Interactions. IEEE Trans. Robotics 33(4): 994-1001 (2017) - [j83]Jeannette Bohg, Karol Hausman, Bharath Sankaran, Oliver Brock, Danica Kragic, Stefan Schaal, Gaurav S. Sukhatme:
Interactive Perception: Leveraging Action in Perception and Perception in Action. IEEE Trans. Robotics 33(6): 1273-1291 (2017) - [c241]Yevgen Chebotar, Karol Hausman, Oliver Kroemer, Gaurav S. Sukhatme, Stefan Schaal:
Regrasping Using Tactile Perception and Supervised Policy Learning. AAAI Spring Symposia 2017 - [c240]Yevgen Chebotar, Karol Hausman, Marvin Zhang, Gaurav S. Sukhatme, Stefan Schaal, Sergey Levine:
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning. ICML 2017: 703-711 - [c239]Stephanie Kemna, John G. Rogers, Carlos Nieto-Granda, Stuart Young, Gaurav S. Sukhatme:
Multi-robot coordination through dynamic Voronoi partitioning for informative adaptive sampling in communication-constrained environments. ICRA 2017: 2124-2130 - [c238]James A. Preiss, Wolfgang Hönig, Gaurav S. Sukhatme, Nora Ayanian:
Crazyswarm: A large nano-quadcopter swarm. ICRA 2017: 3299-3304 - [c237]Kai-Chieh Ma, Lantao Liu, Gaurav S. Sukhatme:
Informative planning and online learning with sparse Gaussian processes. ICRA 2017: 4292-4298 - [c236]Oliver Kroemer, Gaurav S. Sukhatme:
Feature selection for learning versatile manipulation skills based on observed and desired trajectories. ICRA 2017: 4713-4720 - [c235]James A. Preiss, Wolfgang Hönig, Nora Ayanian, Gaurav S. Sukhatme:
Downwash-aware trajectory planning for large quadrotor teams. IROS 2017: 250-257 - [c234]Eric Heiden, Karol Hausman, Gaurav S. Sukhatme, Ali-akbar Agha-mohammadi:
Planning high-speed safe trajectories in confidence-rich maps. IROS 2017: 2880-2886 - [c233]Zhibei Ma, Kai Yin, Lantao Liu, Gaurav S. Sukhatme:
A spatio-temporal representation for the orienteering problem with time-varying profits. IROS 2017: 6785-6792 - [c232]Shoubhik Debnath, Lantao Liu, Gaurav S. Sukhatme:
Reachability and Differential Based Heuristics for Solving Markov Decision Processes. ISRR 2017: 387-404 - [c231]Ali-akbar Agha-mohammadi, Eric Heiden, Karol Hausman, Gaurav S. Sukhatme:
Confidence-Rich Grid Mapping. ISRR 2017: 623-641 - [c230]Karol Hausman, Yevgen Chebotar, Stefan Schaal, Gaurav S. Sukhatme, Joseph J. Lim:
Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets. NIPS 2017: 1235-1245 - [c229]James A. Preiss, Karol Hausman, Gaurav S. Sukhatme, Stephan Weiss:
Trajectory Optimization for Self-Calibration and Navigation. Robotics: Science and Systems 2017 - [i17]