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🚨 Robots are learning to personalize household tasks, like tidying up, based on your preferences.
Using just a few examples, this system, developed by a team from Princeton, can figure out where you like things—like putting shirts in drawers or on shelves—by combining language-based planning with AI-powered learning.
Tested on TidyBot, a real-world robot, this method achieves 91.2% accuracy on new objects and successfully tidies 85% of items in real-life scenarios.
Personalized robot assistants are getting closer to becoming a reality!
Using just a few examples, this system, developed by a team from Princeton, can figure out where you like things—like putting shirts in drawers or on shelves—by combining language-based planning with AI-powered learning.
Tested on TidyBot, a real-world robot, this method achieves 91.2% accuracy on new objects and successfully tidies 85% of items in real-life scenarios.
Personalized robot assistants are getting closer to becoming a reality!