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cs.RO2023★ 103 cited
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
cs.RO2023★ 5 cited
Lan-grasp: Using Large Language Models for Semantic Object Grasping and Placement
Reihaneh Mirjalili, Michael Krawez, Yannik Blei +3
In this paper, we propose Lan-grasp, a novel approach towards more appropriate semantic grasping and placing. We leverage foundation models to equip the robot with a semantic under…