If you’ve ever needed any proof that robots will be a permanent part of our future, then here it is. Researchers at Columbia University in the United States have developed an experimental prototype of the world’s first smiling robot.
Yes, that’s right – a robot that will smile back at you. Now, before you start to unpack your copies of Westworld or Terminator to show that cyborgs and robots may one day run amok to conquer the world and wreak terrible retribution on their inventors there are a couple of things you need to know.
Firstly, this is an experimental project that has thus far only worked in laboratory conditions. It needs much more development before it can be rolled out into everyday life.
And secondly, it might be a promising idea that machines at least give the impression that they understand and can express human emotions.
The truth is that robots will be a huge part of our technological future. Already we see nuts and bolts marvels becoming indispensable in our, in warehouses, in factories and even in the operating rooms of our biggest hospitals.
The thought that a robot might be able to operate on your appendix some time in the near future is no longer a thought bubble in a science fiction writer’s imagination, but a reality coming to a surgery near you sooner than you think.
Which means that humans and robots are going to be working side by side on a large scale some time in the next few decades.
Humans convey as much as 60 per cent of their communication through other than speech. Words only convey a part of the message. If a phrase is delivered with a smile, then it has a different meaning to a phrase delivered through gritted teeth or with no expression whatsoever.
And while robots might not need to read emotions in the same way humans do, humans need to be able to trust those who work beside or closely with them.
With the increasing use of robots in locations where robots and humans need to work closely together, from nursing homes to warehouses and factories, the need for a more responsive, facially realistic robot is growing more urgent.
Long interested in the interactions between robots and humans, researchers in the Creative Machines Lab at Columbia Engineering have been working for five years to create EVA, a new autonomous robot with a soft and expressive face that responds to match the expressions of nearby humans.
“The idea for EVA took shape a few years ago, when my students and I began to notice that the robots in our lab were staring back at us through plastic, googly eyes,” says Hod Lipson, Professor of Innovation (Mechanical Engineering) and director of the Creative Machines Lab at Columbia University in the United States.
Lipson set off on his path to discovery when he visited a grocery store, where he encountered restocking robots wearing name badges, and in one case, decked out in a cosy, hand-knit cap.
“People seemed to be humanizing their robotic colleagues by giving them eyes, an identity, or a name,” he says. “This made us wonder, if eyes and clothing work, why not make a robot that has a super-expressive and responsive human face?”
While this sounds simple, creating a convincing robotic face has been a formidable challenge for roboticists. For decades, robotic body parts have been made of metal or durable plastic, materials that were too stiff to flow and move the way human tissue does. Robotic hardware has been similarly crude and difficult to work with–circuits, sensors, and motors are heavy, power-intensive, and bulky.
The first phase of the project began in Lipson’s lab several years ago when undergraduate student Zanwar Faraj led a team of students in building the robot’s physical “machinery.”
They constructed EVA as a disembodied bust that bears a strong resemblance to the silent but facially animated performers of the Blue Man Group.
EVA can express the six basic emotions of anger, disgust, fear, joy, sadness, and surprise, as well as an array of more nuanced emotions, by using artificial “muscles” (i.e. cables and motors) that pull on specific points on EVA’s face, mimicking the movements of the more than 42 tiny muscles attached at various points to the skin and bones of human faces.
“The greatest challenge in creating EVA was designing a system that was compact enough to fit inside the confines of a human skull while still being functional enough to produce a wide range of facial expressions,” Faraj says.
To overcome this challenge, the team relied heavily on 3D printing to manufacture parts with complex shapes that integrated seamlessly and efficiently with EVA’s skull. After weeks of tugging cables to make EVA smile, frown, or look upset, the team noticed that EVA’s blue, disembodied face could elicit emotional responses from their lab mates.
“I was minding my own business one day when EVA suddenly gave me a big, friendly smile,” Lipson recalled. “I knew it was purely mechanical, but I found myself reflexively smiling back.”
Once the team was satisfied with EVA’s “mechanics,” they began to address the project’s second major phase: programming the artificial intelligence that would guide EVA’s facial movements. While lifelike animatronic robots have been in use at theme parks and in movie studios for years, Lipson’s team made two technological advances. EVA uses deep learning artificial intelligence to “read” and then mirror the expressions on nearby human faces. And EVA’s ability to mimic a wide range of different human facial expressions is learned by trial and error from watching videos of itself.
The most difficult human activities to automate involve non-repetitive physical movements that take place in complicated social settings.
Boyuan Chen, Lipson’s PhD student who led the software phase of the project, quickly realized that EVA’s facial movements were too complex a process to be governed by pre-defined sets of rules.
To tackle this challenge, Chen and a second team of students created EVA’s brain using several Deep Learning neural networks.
The robot’s brain needed to master two capabilities: one, to learn to use its own complex system of mechanical muscles to generate any facial expression, and two, to know which faces to make by “reading” the faces of humans.
To teach EVA what its own face looked like, Chen and team filmed hours of footage of EVA making a series of random faces. Then, like a human watching herself on Zoom, EVA’s internal neural networks learned to pair muscle motion with the video footage of its own face.
Now that EVA had a primitive sense of how its own face worked (known as a “self-image”), it used a second network to match its own self-image with the image of a human face captured on its video camera.
After several refinements and iterations, EVA acquired the ability to read human face gestures from a camera, and to respond by mirroring that human’s facial expression.
The researchers note that EVA is a laboratory experiment, and mimicry alone is still a far cry from the complex ways in which humans communicate using facial expressions.
But such enabling technologies could someday have beneficial, real-world applications. For example, robots capable of responding to a wide variety of human body language would be useful in workplaces, hospitals, schools, and homes.
“There is a limit to how much we humans can engage emotionally with cloud-based chatbots or disembodied smart-home speakers,” says Lipson. “Our brains seem to respond well to robots that have recognizable physical presence.
Even more importantly, says Boyuan Chen, it helps human build a little faith in their technological colleagues: “Robots are intertwined in our lives in a growing number of ways, so building trust between humans and machines is increasingly important.”
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