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TU Darmstadt, Honda Research Institute Europe, Columbia University
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Automating the RL workflow with HARBOR cuts engineering costs and enhances policy transferability to real-world robots.
Standard LLMs can now perform complex bimanual robot manipulation tasks with impressive success rates, all without any task-specific training.
Robots can now achieve superior surface coverage with precise end-effector poses thanks to a new SE(3)-aware Stein Variational Gradient Descent method that outperforms existing trajectory optimization techniques.
