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QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation., , , , , , , , , and 1 other author(s). CoRR, (2018)Thinking While Moving: Deep Reinforcement Learning with Concurrent Control., , , , , , and . ICLR, OpenReview.net, (2020)Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks., , , , , , , , and . CoRR, (2018)Hybrid Random Features., , , , , , , , , and 3 other author(s). CoRR, (2021)RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control., , , , , , , , , and 44 other author(s). CoRR, (2023)Visionary: Vision architecture discovery for robot learning., , , , , , , and . ICRA, page 10779-10785. IEEE, (2021)Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation., , , , , , , , , and 7 other author(s). CoRL, volume 205 of Proceedings of Machine Learning Research, page 1708-1721. PMLR, (2022)Do As I Can, Not As I Say: Grounding Language in Robotic Affordances., , , , , , , , , and 33 other author(s). CoRR, (2022)Disentangled Planning and Control in Vision Based Robotics via Reward Machines., , , , and . CoRR, (2020)Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks., , , , , , , , and . CVPR, page 12627-12637. Computer Vision Foundation / IEEE, (2019)