Cornell Scientists Create ‘Robo Brain’ to Teach Robots to Learn from Humans
Two researchers have created “Robo Brain” — a large-scale computational system that learns from publicly available Internet resources — to teach robots how humans naturally behave.
The exclusive data bank for robots will help the machines learn how to find keys, pour a drink, put away dishes, and when not to interrupt two people having a conversation.
“Our laptops and cellphones have access to all the information we want. If a robot encounters a situation it has not seen before, it can query ‘Robo Brain’ in the cloud,” explained lead researcher Ashutosh Saxena, an assistant professor of computer science at Cornell University in New York.
“Robo Brain” is currently downloading and processing about 1 billion images, 120,000 YouTube videos, and 100 million how-to documents and appliance manuals.
“The information is being translated and stored in a robot-friendly format that robots will be able to draw on when they need it,” Saxena added.
According to him, “Robo Brain” will process images to pick out the objects in them, and by connecting images and video with text, it will learn to recognize objects and how they are used, along with human language and behavior.
For example, if a robot sees a coffee mug, it can learn from “Robo Brain” not only that it is a coffee mug but also that liquids can be poured into or out of it, that it can be grasped by the handle, and that it must be carried upright when it is full.
“The ‘Robo Brain’ will look like a gigantic, branching graph with abilities for multi-dimensional queries,” explained Aditya Jami, a visiting researcher at Cornell who designed the large-scale database for the brain.
Like a human learner, “Robo Brain” will have teachers thanks to crowdsourcing, said Saxena, who described the project at the 2014 Robotics: Science and Systems Conference in Berkeley recently.