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MIT engineers and New York University researchers introduce FLEX, a flexible feature-editing pipeline for robot motion-planning presented at the annual Conference on Robot Learning this month. The system uses GPT-4o to help robots interpret human natural language commands by adding, generalizing, and masking features to avoid spills or drops on fragile items like laptops and mugs during simulated tasks.
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