Karol Hausman

发表

Interactive Perception: Leveraging Action in Perception and Perception in Action

Oliver Brock, Gaurav S. Sukhatme, Danica Kragic, 2016, IEEE Transactions on Robotics.

Simulator Predictive Control: Using Learned Task Representations and MPC for Zero-Shot Generalization and Sequencing

Gaurav S. Sukhatme, Stefan Schaal, Karol Hausman, 2018 .

Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning

Gaurav S. Sukhatme, Karol Hausman, Ryan Julian, 2020 .

Active articulation model estimation through interactive perception

Gaurav S. Sukhatme, Karol Hausman, Scott Niekum, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

Slip Detection and Classification for Grip Control using Multiple Sensory Modalities on a Biomimetic Tactile Sensor

Yevgen Chebotar, Artem Molchanov, Karol Hausman, 2015 .

Learning to Interactively Learn and Assist pdf

Karol Hausman, Chelsea Finn, Mark Woodward, 2019, AAAI.

Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning pdf

Karol Hausman, Sergey Levine, Vikash Kumar, 2020, Robotics: Science and Systems.

Towards Interactive Object Recognition

Gaurav S. Sukhatme, Fei Sha, Karol Hausman, 2014 .

Gradient Surgery for Multi-Task Learning pdf

Karol Hausman, Abhishek Gupta, Chelsea Finn, 2020, NeurIPS.

Mint: Matrix-Interleaving for Multi-Task Learning

Sergey Levine, Karol Hausman, Abhishek Gupta, 2019 .

Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation pdf

Gaurav S. Sukhatme, Karol Hausman, Ryan Julian, 2020, RSS 2020.

Generalizing Regrasping with Supervised Policy Learning

Gaurav S. Sukhatme, Oliver Kroemer, Stefan Schaal, 2016, ISER.

Cooperative multi-robot control for target tracking with onboard sensing 1

Gaurav S. Sukhatme, Karol Hausman, Nora Ayanian, 2015, Int. J. Robotics Res..

Cooperative Control for Target Tracking with Onboard Sensing

Gaurav S. Sukhatme, Karol Hausman, Nora Ayanian, 2014, ISER.

Modeling Long-horizon Tasks as Sequential Interaction Landscapes pdf

Karol Hausman, Soren Pirk, Mohi Khansari, 2020, CoRL.

Dynamics-Aware Unsupervised Discovery of Skills pdf

Sergey Levine, Karol Hausman, Vikash Kumar, 2019, ICLR.

Demystifying Reproducibility in Meta- and Multi-Task Reinforcement Learning

Gaurav S. Sukhatme, Karol Hausman, Zhanpeng He, 2020, ICML 2020.

Tracking-based interactive segmentation of textureless objects

Zoltan-Csaba Marton, Dejan Pangercic, Karol Hausman, 2013, 2013 IEEE International Conference on Robotics and Automation.

Force Estimation and Slip Detection for Grip Control using a Biomimetic Tactile Sensor

Gaurav S. Sukhatme, Yevgen Chebotar, Artem Molchanov, 2015 .

Region Growing Curriculum Generation for Reinforcement Learning pdf

Gaurav S. Sukhatme, Artem Molchanov, Karol Hausman, 2018, ArXiv.

BiGS: BioTac Grasp Stability Dataset

Gaurav S. Sukhatme, Oliver Kroemer, Stefan Schaal, 2016 .

Dynamics-Aware Unsupervised Skill Discovery

Karol Hausman, Sergey Levine, Vikash Kumar, 2020, ICLR 2020.

Confidence-rich grid mapping

Karol Hausman, Ali-akbar Agha-mohammadi, Eric Heiden, 2019, Int. J. Robotics Res..

Force estimation and slip detection/classification for grip control using a biomimetic tactile sensor

Gaurav S. Sukhatme, Stefan Schaal, Yevgen Chebotar, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Slip Classification Using Tangential and Torsional Skin Distortions on a Biomimetic Tactile Sensor

Gaurav S. Sukhatme, Stefan Schaal, Yevgen Chebotar, 2015 .

IntentionGAN: MultiModal Imitation Learningfrom Unstructured Demonstrations

Gaurav S. Sukhatme, Stefan Schaal, Yevgen Chebotar, 2017 .

Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning

Gaurav S. Sukhatme, Sergey Levine, Stefan Schaal, 2017, ICML.

Confidence-Rich Grid Mapping

Gaurav S. Sukhatme, Karol Hausman, Ali-akbar Agha-mohammadi, 2017, ISRR.

Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping pdf

Karol Hausman, Mrinal Kalakrishnan, Adrian Li, 2019, Robotics: Science and Systems.

Observability-Aware Trajectory Optimization for Self-Calibration With Application to UAVs

Gaurav S. Sukhatme, Karol Hausman, Stephan Weiss, 2016, IEEE Robotics and Automation Letters.

Learning Robot Skill Embeddings

Karol Hausman, Martin A. Riedmiller, Jost Tobias Springenberg, 2017, NIPS 2017.

Learning an Embedding Space for Transferable Robot Skills

Karol Hausman, Martin A. Riedmiller, Jost Tobias Springenberg, 2018, ICLR.

High-speed Safe Trajectory Planning in Confidence-rich Maps

Gaurav S. Sukhatme, Karol Hausman, Ali-akbar Agha-mohammadi, 2017, IROS 2017.

Interactive Segmentation of Textured and Textureless Objects

Gaurav S. Sukhatme, Zoltan-Csaba Marton, Dejan Pangercic, 2015 .

Cooperative Multi-Robot Control for Target Tracking with Efficient Switching of Onboard Sensing Topologies

Gaurav S. Sukhatme, Karol Hausman, Nora Ayanian, 2014 .

A Geometric Perspective on Self-Supervised Policy Adaptation pdf

Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski, 2020, ArXiv.

Simultaneous self-calibration and navigation using trajectory optimization

Gaurav S. Sukhatme, Karol Hausman, Stephan Weiss, 2018, Int. J. Robotics Res..

Self-supervised regrasping using spatio-temporal tactile features and reinforcement learning

Gaurav S. Sukhatme, Stefan Schaal, Yevgen Chebotar, 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Regrasping Using Tactile Perception and Supervised Policy Learning

Gaurav S. Sukhatme, Oliver Kroemer, Stefan Schaal, 2017, AAAI Spring Symposia.

Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets

Gaurav S. Sukhatme, Stefan Schaal, Yevgen Chebotar, 2017, NIPS.

Optimization-based Cooperative Multi-Robot Target Tracking with Reasoning about Occlusions

Gaurav S. Sukhatme, Karol Hausman, Ken Goldberg, 2015 .

IntentionGAN: MultiTask Imitation Learningfrom Unstructured Demonstrations

Yevgen Chebotar, Karol Hausman, Joseph J. Lim, 2017 .

Scaling simulation-to-real transfer by learning a latent space of robot skills

Karol Hausman, Joseph J. Lim, Eric Heiden, 2020 .

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control pdf

Karol Hausman, Julian Ibarz, Sergey Levine, 2020, ICLR.

Training an Interactive Helper pdf

Karol Hausman, Chelsea Finn, Mark Woodward, 2019, ArXiv.

Trajectory Optimization for Self-Calibration and Navigation

Gaurav S. Sukhatme, Karol Hausman, Stephan Weiss, 2017, Robotics: Science and Systems.

Combining Model-Based and Model-Free Updates for Deep Reinforcement Learning

Gaurav S. Sukhatme, Sergey Levine, Stefan Schaal, 2017 .

Segmentation of Textured and Textureless Objects through Interactive Perception

Kei Okada, Zoltan-Csaba Marton, Dejan Pangercic, 2012 .

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

Sergey Levine, Karol Hausman, Zhanpeng He, 2019, CoRL.

Self-calibrating multi-sensor fusion with probabilistic measurement validation for seamless sensor switching on a UAV

Gaurav S. Sukhatme, Larry H. Matthies, Roland Brockers, 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

Learning a System-ID Embedding Space for Domain Specialization with Deep Reinforcement Learning

Gaurav S. Sukhatme, Karol Hausman, James A. Preiss, 2018 .

Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning

Sergey Levine, Karol Hausman, Corey Lynch, 2019, CoRL.

Scaling simulation-to-real transfer by learning composable robot skills

Gaurav S. Sukhatme, Stefan Schaal, Karol Hausman, 2018, ISER.

Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations pdf

Gaurav S. Sukhatme, Stefan Schaal, Karol Hausman, 2018, ArXiv.

Confidence-aware Occupancy Grids

Gaurav S. Sukhatme, Karol Hausman, Ali-akbar Agha-mohammadi, 2017, IROS 2017.

Occlusion-aware multi-robot 3D tracking

Gaurav S. Sukhatme, Karol Hausman, Pieter Abbeel, 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Planning high-speed safe trajectories in confidence-rich maps

Gaurav S. Sukhatme, Karol Hausman, Ali-akbar Agha-mohammadi, 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Autonomous Reinforcement Learning: Formalism and Benchmarking pdf

Sergey Levine, Karol Hausman, Chelsea Finn, 2021, ArXiv.

Persistent Reinforcement Learning via Subgoal Curricula pdf

Sergey Levine, Karol Hausman, Chelsea Finn, 2021, ArXiv.

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills pdf

Sergey Levine, Yevgen Chebotar, Karol Hausman, 2021, ICML.

A Metric Space Perspective on Self-Supervised Policy Adaptation

Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski, 2021, IEEE Robotics and Automation Letters.

Conservative Data Sharing for Multi-Task Offline Reinforcement Learning pdf

Sergey Levine, Yevgen Chebotar, Karol Hausman, 2021, NeurIPS.

AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale pdf

Sergey Levine, Yevgen Chebotar, Karol Hausman, 2021, CoRL.

Autonomous Reinforcement Learning via Subgoal Curricula

Sergey Levine, Karol Hausman, Chelsea Finn, 2021, NeurIPS.

MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale pdf

Sergey Levine, Yevgen Chebotar, Karol Hausman, 2021, ArXiv.

Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping pdf

Karol Hausman, Mrinal Kalakrishnan, Adrian Li, 2019, Robotics: Science and Systems.

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning pdf

Sergey Levine, Karol Hausman, Zhanpeng He, 2019, CoRL.