When it comes to learning how to cook, robots and humans have something in common: We both turn to YouTube for online tutorials on how to chop garlic or how to whisk mashed potatoes. Human are interested in actually eating the food, but one group scientists has a different goal in mind.
Researchers at the University of Maryland, funded by the DARPA's Mathematics of Sensing, Exploitation and Execution (MSEE), are teaching robots how to process visual data and to learn from what they see. The robots that were shown cooking videos were able to grab and manipulate the correct kitchen tools and use them to complete specific tasks with great accuracy, according to DARPA, which stands for Defense Advanced Research Projects Agency. And, this exercise requires no additional programming from humans. The robots learned how to complete tasks, such as picking up a pitcher, and to put that new knowledge into practice in the physical world.
Reza Ghanadan, program manager in DARPA's Defense Sciences Offices, said about the research, "The MSEE program initially focused on sensing, which involves perception and understanding of what’s happening in a visual scene, not simply recognizing and identifying objects. We've now taken the next step to execution, where a robot processes visual cues through a manipulation action-grammar module and translates them into actions."
"This system allows robots to continuously build on previous learning — such as types of objects and grasps associated with them — which could have a huge impact on teaching and training," explained Ghanadan. "Instead of the long and expensive process of programming code to teach robots to do tasks, this research opens the potential for robots to learn much faster, at much lower cost and, to the extent they are authorized to do so, share that knowledge with other robots. This learning-based approach is a significant step towards developing technologies that could have benefits in areas such as military repair and logistics."
This ability to perform a task after observing it being done marks a huge leap forward in the field of robotics. And, according to Yiannis Aloimonos, University of Maryland professor of computer science and director of the Computer Vision Lab, cooking was the perfect skill to test the robots' progress.
"We chose cooking videos because everyone has done it and understands it," said Aloimonos. "But cooking is complex in terms of manipulation, the steps involved and the tools you use. If you want to cut a cucumber, for example, you need to grab the knife, move it into place, make the cut and observe the results to make sure you did them properly."
The researchers aren't interested in just copying movements. They want to give robots the ability to complete goal-oriented actions without the time-intensive process of programming that act into the robot’s system. This could potentially save humans from doing dangerous work by sending robots in their place. Aloimonos envisions a future in which robots are able to defuse bombs and clean up nuclear disasters.
"By having flexible robots, we're contributing to the next phase of automation. This will be the next industrial revolution," said the researchers.
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