Bohg, Jeannette

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2,676

Data-Driven Grasp Synthesis—A Survey

Bohg, J., Morales, A., Asfour, T., & Kragic, D. (2014) · IEEE Transactions on Robotics

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 929

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

Lee, M. A., Zhu, Y., Srinivasan, K., Shah, P., Savarese, S., Fei-Fei, L., Garg, A., & Bohg, J. (2019) · 2019 International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 349

Interactive perception: Leveraging action in perception and perception in action

Bohg, J., Hausman, K., Sankaran, B., Brock, O., Kragic, D., Schaal, S., & Sukhatme, G. S. (2017) · IEEE Transactions on Robotics

Robot Manipulation and LearningRobotics and Sensor-Based Localization

Cited by 227

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

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

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

Consistency Policy: Accelerated Visuomotor Policies via Consistency Distillation

Prasad, A., Lin, K., Wu, J., Zhou, L., & Bohg, J. (2024) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 57

Multimodal Sensor Fusion with Differentiable Filters

Lee, M. A., Yi, B., Martin-Martin, R., Savarese, S., & Bohg, J. (2020) · 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Target Tracking and Data Fusion in Sensor NetworksRobot Manipulation and Learning

Cited by 46

XIRL: Cross-embodiment inverse reinforcement learning

Zakka, K., Zeng, A., Florence, P., Tompson, J., Bohg, J., & Dwibedi, D. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 38

Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors

Lee, M. A., Tan, M., Zhu, Y., & Bohg, J. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 24

Learning Periodic Tasks from Human Demonstrations

Yang, J., Zhang, J., Settle, C., Rai, A., Antonova, R., & Bohg, J. (2022) · 2022 International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 21

Big Data on Robotics

Bohg, J., Ciocarlie, M., Civera, J., & Kavraki, L. E. (2016) · Big Data

Robotics and Automated SystemsBig Data Technologies and Applications

Cited by 3