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๐Ÿ“š Researchers at Stanford Propose TRANSIC: A Human-in-the-Loop Method to Handle the Sim-to-Real Transfer of Policies for Contact-Rich Manipulation Tasks


๐Ÿ’ก Newskategorie: AI Nachrichten
๐Ÿ”— Quelle: marktechpost.com

Learning in simulation and applying the learned policy to the real world is a potential approach to enable generalist robots, and solve complex decision-making tasks. However, the challenge to this approach is to address simulation-to-reality (sim-to-real) gaps. Also, a huge amount of data is needed while learning to solve these tasks, and the load of [โ€ฆ]

The post Researchers at Stanford Propose TRANSIC: A Human-in-the-Loop Method to Handle the Sim-to-Real Transfer of Policies for Contact-Rich Manipulation Tasks appeared first on MarkTechPost.

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