What if robots could learn complex manipulation tasks and self-correct, all without costly real-world errors? Researchers from Hong Kong University of Science and Technology and ByteDance Seed present WMPO (World-Model-based Policy Optimization). This new framework lets
WMPO enables robots to learn complex tasks without real-world errors
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