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lbr-iiwa

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PetropoulakisPanagiotis / igae

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State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Grasping

python computer-vision unity deep-reinforcement-learning embeddings lbr-iiwa segmentation robotiq autoencoders end-to-end-learning gym-environment sim2real ppo-agent reward-engineering sim-to-real stablebaselines3 robotic-grasping state-representation incentivized-grasping-autoencoder state-randomization
  • Updated Aug 15, 2024
  • Python

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