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Nov 1, 2021 · We provide a comprehensive review of sim-to-real research for robotics, focusing on a technique named 'domain randomization' which is a method for learning from randomized …
Domain Randomization (DR) is the sim-to-real approach that varies simulator parameters according to a given distribution at training time (Muratore et al., 2022b), effectively inducing an additional …
Mar 18, 2024 · Domain Randomization (DR) is commonly used for sim2real transfer of reinforcement learning (RL) policies in robotics. Most DR approaches require a simulator with a …
Domain Randomization for Robust, Affordable and Effective Closed-Loop Control of Soft Robots Abstract: Soft robots are gaining popularity thanks to their intrinsic safety to contacts and …
Domain randomisation is a very popular method for visual sim-to-real transfer in robotics, due to its simplicity and ability to achieve transfer without any real-world images at all. Nonetheless, a …
Mar 7, 2023 · We provide an extensive evaluation in simulation on four different tasks and two soft robot designs, opening interesting perspectives for future research on Reinforcement Learning …
Towards Real-World Efficiency: Domain Randomization in Reinforcement Learning for Pre-Capture of Free-Floating Moving Targets by Autonomous Robots Published in: 2024 IEEE International …
Oct 18, 2024 · Domain Randomization (DR) is commonly used for sim2real transfer of reinforcement learning (RL) policies in robotics. Most DR approaches require a simulator with a fixed set of …
Abstract Domain randomization in reinforcement learning is an established technique for increasing the ro-bustness of control policies trained in simulation. By randomizing environment properties …
Accepted for presentation at the IEEE IROS 2024 conference in Abu Dhabi Domain Randomization (DR) is commonly used for sim2real transfer of reinforcement learning (RL) policies in robotics. …
Feb 3, 2025 · Domain randomization in reinforcement learning is an established technique for increasing the robustness of control policies trained in simulation. By randomizing environment …
Jan 25, 2024 · In this work, we present a thorough investigation of Domain Randomization in the context of closed-loop soft robot control. We include the examination of existing DR techniques …
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