Hansen, Nicklas

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

Generalization in Reinforcement Learning by Soft Data Augmentation

Hansen, N., & Wang, X. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 111

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

Temporal Difference Learning for Model Predictive Control

Hansen, N., Wang, X., & Su, H. (2022) · arXiv

Reinforcement Learning in RoboticsAdvanced Control Systems Optimization

Cited by 50

MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation

Lancaster, P., Hansen, N., Rajeswaran, A., & Kumar, V. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 8

TD-MPC2: Scalable, Robust World Models for Continuous Control

Hansen, N., Su, H., & Wang, X. (2023) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 8

Finetuning Offline World Models in the Real World

Feng, Y., Hansen, N., Xiong, Z., Rajagopalan, C., & Wang, X. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 2

PWM: Policy learning with multi-task world models

Georgiev, I., Giridhar, V., Hansen, N., & Garg, A. (2024) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 0