Balakrishna, Ashwin

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

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

Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks

Thananjeyan, B., Balakrishna, A., Rosolia, U., Li, F., McAllister, R., Gonzalez, J. E., Levine, S., Borrelli, F., & Goldberg, K. (2020) · IEEE Robotics and Automation Letters

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 83

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

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

OpenVLA: An Open-Source Vision-Language-Action Model

Kim, M. J., Pertsch, K., Karamcheti, S., Xiao, T., Balakrishna, A., Nair, S., Rafailov, R., Foster, E., Lam, G., Sanketi, P., et al. (2024) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 62

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

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

Disentangling Dense Multi-Cable Knots

Viswanath, V., Grannen, J., Sundaresan, P., Thananjeyan, B., Balakrishna, A., Novoseller, E., Ichnowski, J., Laskey, M., Gonzalez, J. E., & Goldberg, K. (2021) · 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robot Manipulation and LearningSoft Robotics and Applications

Cited by 21

Orienting Novel 3D Objects Using Self-Supervised Learning of Rotation Transforms

Devgon, S., Ichnowski, J., Balakrishna, A., Zhang, H., & Goldberg, K. (2020) · 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)

Robot Manipulation and LearningAdvanced Neural Network Applications

Cited by 11

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Abeyruwan, S., Ainslie, J., Alayrac, J.-B., Arenas, M. G., Armstrong, T., Balakrishna, A., Baruch, R., Bauza, M., Blokzijl, M., et al. (2025) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 8

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models

Karamcheti, S., Nair, S., Balakrishna, A., Liang, P., Kollar, T., & Sadigh, D. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 7

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. E., & Goldberg, K. (2021) · arXiv

Robot Manipulation and LearningSoft Robotics and Applications

Cited by 0