In testing, TidyBot correctly determined the category of objects and where to put them—as in, place toys in the box and put clothes on floor—for 85% of objects.
Credit: Princeton Engineering News
A multi-institutional team of engineers mated a mobile robotic arm to a vision model and a large language model to create the TidyBot cleaning robot.
The robot's arm is attached to a wheeled base; its pincer hand can open drawers and retrieve objects, enabling it to carefully put dishes in the sink or toss clothes onto a laundry pile.
TidyBot can differentiate between types of objects with its combined camera/vision model, and the large language model with which it is programmed allows it to learn how carefully or casually it can handle different items.
The robot was 85% accurate in categorizing objects and where to put them.
From Princeton Engineering News
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