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Información - Sim-to-Real Transfer in Robotics
Anchor Critics for Robust Sim-to-Real Transfer in Reinforcement Learning
Anchor Critics, a novel method leveraging dual Q-values from both simulated and real-world data, effectively mitigates catastrophic forgetting in reinforcement learning, enabling robust sim-to-real transfer for robotic control tasks, particularly demonstrated in quadrotor flight control.
Exploring Sim-to-Real Transfer in Robotic Manipulation with TIAGo and Nvidia Simulators
The authors investigate policy-learning approaches for sim-to-real transfer in robotic manipulation using TIAGo and Nvidia simulators, emphasizing collision-less movement in both simulation and real environments.
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