Your lazy teenager problem could soon be solved, thanks to TidyBot.<br /><br />Researchers at Princeton University have developed robots that can spruce up rooms by picking up objects and putting them away.<br /><br />Useful demonstrations have included sorting laundry into lights and darks, identifying recyclable drink cans and putting items where they belong.<br /><br />The clever bot is also seen placing toys into a drawer and even accurately tossing drink cans into the bin.<br /><br />Princeton's School of Engineering explain: "For a robot to personalise physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios.<br /><br />"In this work, we investigate personalisation of household cleanup with robots that can tidy up rooms by picking up objects and putting them away."<br /><br />The team say a key challenge is determining the proper place to put each object, as people's preferences can vary greatly depending on personal taste or cultural background.<br /><br />"For instance, one person may prefer storing shirts in the drawer, while another may prefer them on the shelf," they add.<br /><br />The researchers aim to build systems that can learn such preferences from just a handful of examples via prior interactions with a particular person.<br /><br />They created TidyBot, a real-world mobile manipulator, to test the theory. It managed to successfully put away 85% of objects in real-world test scenarios.<br /><br />The team say: "We aim to build systems that can learn such preferences from just a handful of examples via prior interactions with a particular person.<br /><br />"We show that robots can combine language-based planning and perception with the few-shot summarisation capabilities of large language models (LLMs) to infer generalised user preferences that are broadly applicable to future interactions.<br /><br />"This approach enables fast adaptation and achieves 91.2% accuracy on unseen objects in our benchmark dataset."
