There have been a plethora of movies in the last few decades about robots becoming smarter and more advanced and eventually taking over the world. While we are a long way from that feasibly taking place, researchers have made developments that enables teaching robots to cook or perform other tasks by watching videos. A research project by local digital research body National ICT Australia (NICTA) and the University of Maryland is focused on giving robots an ability to learn any movement sequence and repeat it.
The project in Australia is being led by Dr Yi Li, NICTA senior researcher in computer vision. The robots are learning to undertake cooking tasks such as baking cakes, making salads and flipping burgers by simply watching cooking videos on YouTube. Dr Li said a robot could learn movements and identify objects such as a mixing bowl or spatula by analysing pixels in the video downloaded to it. It was then able to repeat the behaviour. Scientists are teaching robots to learn essentially any functionality from the real, physical world.
So far the cooking robot had watched 88 videos and is capable of picking up and turning around objects, and pour, mix and flip objects like a burger. It can’t quite enact full recipes yet, as it hasn’t learnt the skill of cutting objects.
Dr Li said the robot could, in approximately 5 to 10 years, be capable of cleaning rooms, packing things up, doing housework and even water the plants or feed the fish when you are away on holiday. Li stressed the importance of the robot not only identifying movements but also learning the purpose behind the action. He said, “if we can understand some high-level purpose, we can have different implementations, different variations.”
The project of developing a deep-learning project began at NICTA in late 2012, comprising of Dr Li, two in-house PhD students, and three overseas students. The robot research was presented this month in Austin, Texas at the annual conference of the Associated for the Advancement of Artificial Intelligence. Private funding and research in similar areas of robotics could help the desired functionality of the robot be developed sooner.
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