Martín-Martín, Roberto

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

ULIP-2: Towards Scalable Multimodal Pre-Training for 3D Understanding

Xue, L., Yu, N., Zhang, S., Panagopoulou, A., Li, J., Martín-Martín, R., Wu, J., Xiong, C., Xu, R., Niebles, J. C., et al. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisMultimodal Machine Learning Applications

Cited by 144

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

Principles and Guidelines for Evaluating Social Robot Navigation Algorithms

Francis, A., Pérez-D’Arpino, C., Li, C., Xia, F., Alahi, A., Alami, R., Bera, A., Biswas, A., Biswas, J., Chandra, R., et al. (2025) · ACM Transactions on Human-Robot Interaction

Social Robot Interaction and HRIRobotic Path Planning Algorithms

Cited by 107

GTI: Learning to Generalize across Long-Horizon Tasks from Human Demonstrations

Mandlekar, A., Xu, D., Martín-Martín, R., Savarese, S., & Fei-Fei, L. (2020) · Robotics: Science and Systems XVI

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 90

What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Mandlekar, A., Xu, D., Wong, J., Nasiriany, S., Wang, C., Kulkarni, R., Fei-Fei, L., Savarese, S., Zhu, Y., & Martín-Martín, R. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 66

Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems

Eppner, C., Höfer, S., Jonschkowski, R., Martín-Martín, R., Sieverling, A., Wall, V., & Brock, O. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

Robot Manipulation and LearningRobotics and Automated Systems

Cited by 62

iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks

Li, C., Xia, F., Martín-Martín, R., Lingelbach, M., Srivastava, S., Shen, B., Vainio, K., Gokmen, C., Dharan, G., Jain, T., et al. (2021) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 58

BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments

Srivastava, S., Li, C., Lingelbach, M., Martín-Martín, R., Xia, F., Vainio, K., Lian, Z., Gokmen, C., Buch, S., Liu, C. K., et al. (2021) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 55

Learning Multi-Arm Manipulation Through Collaborative Teleoperation

Tung, A., Wong, J., Mandlekar, A., Martín-Martín, R., Zhu, Y., Fei-Fei, L., & Savarese, S. (2020) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 49

Human-in-the-Loop Imitation Learning using Remote Teleoperation

Mandlekar, A., Xu, D., Martín-Martín, R., Zhu, Y., Fei-Fei, L., & Savarese, S. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 35

ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation

Xia, F., Li, C., Martín-Martín, R., Litany, O., Toshev, A., & Savarese, S. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 33

Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulation

Wong, J., Tung, A., Kurenkov, A., Mandlekar, A., Fei-Fei, L., Savarese, S., & Martín-Martín, R. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 19

Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations

Mandlekar, A., Xu, D., Martín-Martín, R., Savarese, S., & Fei-Fei, L. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 17

BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation

Li, C., Zhang, R., Wong, J., Gokmen, C., Srivastava, S., Martín-Martín, R., Wang, C., Levine, G., Ai, W., Martinez, B., et al. (2024) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 6