Goldberg, Ken

Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation

Zhang, T., McCarthy, Z., Jow, O., Lee, D., Chen, X., Goldberg, K., & Abbeel, P. (2017) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 618

Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation

Zhang, T., McCarthy, Z., Jow, O., Lee, D., Chen, X., Goldberg, K., & Abbeel, P. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 609

RLlib: Abstractions for Distributed Reinforcement Learning

Liang, E., Liaw, R., Moritz, P., Nishihara, R., Fox, R., Goldberg, K., Gonzalez, J. E., Jordan, M. I., & Stoica, I. (2017) · arXiv

Reinforcement Learning in RoboticsParallel Computing and Optimization Techniques

Cited by 473

ActiveClean: interactive data cleaning for statistical modeling

Krishnan, S., Wang, J., Wu, E., Franklin, M. J., & Goldberg, K. (2016) · Proceedings of the VLDB Endowment

Machine Learning and Data ClassificationData Quality and Management

Cited by 264

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration 0

O’Neill, A., Rehman, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., Mandlekar, A., Jain, A., et al. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 210

Artificial intelligence meets medical robotics

Yip, M., Salcudean, S., Goldberg, K., Althoefer, K., Menciassi, A., Opfermann, J. D., Krieger, A., Swaminathan, K., Walsh, C. J., Huang, H. (., et al. (2023) · Science

Soft Robotics and ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 207

A Berkeley View of Systems Challenges for AI

Stoica, I., Song, D., Popa, R. A., Patterson, D., Mahoney, M. W., Katz, R., Joseph, A. D., Jordan, M., Hellerstein, J. M., Gonzalez, J. E., et al. (2017) · arXiv

Artificial Intelligence ApplicationsAdvanced Neural Network Applications

Cited by 171

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Khazatsky, A., Pertsch, K., Nair, S., Balakrishna, A., Dasari, S., Karamcheti, S., Nasiriany, S., Srirama, M. K., Chen, L. Y., Ellis, K., et al. (2024) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 159

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Khazatsky, A., Pertsch, K., Nair, S., Balakrishna, A., Dasari, S., Karamcheti, S., Nasiriany, S., Srirama, M., Chen, L., Ellis, K., et al. (2024) · Robotics: Science and Systems XX

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 159

Sim2Real in Robotics and Automation: Applications and Challenges

Hofer, S., Bekris, K., Handa, A., Gamboa, J. C., Mozifian, M., Golemo, F., Atkeson, C., Fox, D., Goldberg, K., Leonard, J., et al. (2021) · IEEE Transactions on Automation Science and Engineering

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 154

Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning

Thananjeyan, B., Garg, A., Krishnan, S., Chen, C., Miller, L., & Goldberg, K. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA)

Surgical Simulation and TrainingReinforcement Learning in Robotics

Cited by 144

Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks

Seita, D., Florence, P., Tompson, J., Coumans, E., Sindhwani, V., Goldberg, K., & Zeng, A. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 130

Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Embodiment Collaboration, O'Neill, A., Rehman, A., Gupta, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 111

Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data

Sundaresan, P., Grannen, J., Thananjeyan, B., Balakrishna, A., Laskey, M., Stone, K., Gonzalez, J. E., & Goldberg, K. (2020) · 2020 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 107

SpeedFolding: Learning Efficient Bimanual Folding of Garments

Avigal, Y., Berscheid, L., Asfour, T., Kröger, T., & Goldberg, K. (2022) · 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robot Manipulation and LearningSoft Robotics and Applications

Cited by 95

A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering

Tanwani, A. K., Mor, N., Kubiatowicz, J., Gonzalez, J. E., & Goldberg, K. (2019) · 2019 International Conference on Robotics and Automation (ICRA)

IoT and Edge/Fog ComputingRobotics and Automated Systems

Cited by 87

DayDreamer: World Models for Physical Robot Learning

Wu, P., Escontrela, A., Hafner, D., Goldberg, K., & Abbeel, P. (2022) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 76

VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric Manipulation

Hoque, R., Seita, D., Balakrishna, A., Ganapathi, A., Tanwani, A., Jamali, N., Yamane, K., Iba, S., & Goldberg, K. (2020) · Robotics: Science and Systems XVI

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 74

A Fog Robotic System for Dynamic Visual Servoing

Tian, N., Chen, J., Ma, M., Zhang, R., Huang, B., Goldberg, K., & Sojoudi, S. (2018) · arXiv

Robotics and Automated SystemsTeleoperation and Haptic Systems

Cited by 49

Visuospatial foresight for physical sequential fabric manipulation

Hoque, R., Seita, D., Balakrishna, A., Ganapathi, A., Tanwani, A. K., Jamali, N., Yamane, K., Iba, S., & Goldberg, K. (2022) · Autonomous Robots

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 45

Applying machine learning to predict future adherence to physical activity programs

Zhou, M., Fukuoka, Y., Goldberg, K., Vittinghoff, E., & Aswani, A. (2019) · BMC Medical Informatics and Decision Making

Physical Activity and HealthMobile Health and mHealth Applications

Cited by 45

LazyDAgger: Reducing Context Switching in Interactive Imitation Learning

Hoque, R., Balakrishna, A., Putterman, C., Luo, M., Brown, D. S., Seita, D., Thananjeyan, B., Novoseller, E., & Goldberg, K. (2021) · 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 31

ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning

Hoque, R., Balakrishna, A., Novoseller, E., Wilcox, A., Brown, D. S., & Goldberg, K. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 31

Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies

Sundaresan*, P., Grannen*, J., Thananjeyan, B., Balakrishna, A., Ichnowski, J., Novoseller, E., Hwang, M., Laskey, M., Gonzalez, J., & Goldberg, K. (2021) · Robotics: Science and Systems XVII

Robot Manipulation and LearningSoft Robotics and Applications

Cited by 26