MRS Bulletin Materials News Podcast

Episode 9: E-skin detects direction of applied pressure

May 03, 2019 Season 1 Episode 9
MRS Bulletin Materials News Podcast
Episode 9: E-skin detects direction of applied pressure
Chapters
MRS Bulletin Materials News Podcast
Episode 9: E-skin detects direction of applied pressure
May 03, 2019 Season 1 Episode 9
MRS Bulletin
E-skin covered in sensors can sense force from multiple directions.
Show Notes

Sophia Chen of MRS Bulletin interviews Zhenan Bao of Stanford University about her research team’s development of a biomimetic soft electronic skin (e-skin) composed of an array of capacitors capable of effectively measuring and discriminating shear force in real time. Read the abstract in Science Robotics. 

CHEN: Zhenan Bao is a professor at Stanford University whose research team developed this robot. She says the key design of the robot is a network of force sensors on its fingertip that tell the robot when to retract. 

BAO: Without sensor feedback, the robot would not know how much it can press on an object before it should stop. 

CHEN: They’ve also shown that the robot can respond to feedback to place a ping-pong ball into an arrangement of different round holes. She says that this type of tactile robot could be useful in all sorts of situations.

BAO: Any robot that will need to have the ability to manipulate objects and being in contact with objects will need this type of sensing feedback.

CHEN: Basically, it works because they’ve invented a stretchable electronic skin covered in sensors that can sense force from multiple directions. It can sense forces perpendicular to the skin, or normal force, as well as forces parallel to the skin, known as shear force. And both forces are necessary for grabbing, holding, and placing objects. Try it. Grab a coin or something between your fingers—you’ll notice how you need to apply pressure to hold it, but also sense shear force to keep it from sliding.  

Previously, electronic skins couldn’t sense shear force very effectively. The sensors were fragile and they also could only be placed sparsely on the robot. But Bao has figured out a way for the robot to sense the shear force, and she’s placed those sensors at high density on the skin. The more sensors crammed onto a surface, the better you can control the robot’s sense of touch.  

Bao says some of the tactile properties of the electronic skin are comparable to the sensitivity of human skin. For example, if the skin experiences a shear pressure increase of 1 pascal, the electronic signal output of the skin will triple in size. 1 Pascal is about the pressure of a dollar bill resting on a table. 

BAO: We are able to use fingertips to feel the most delicate texture and structures on the surface. 

CHEN: In fact, to create this electronic skin, she’s borrowed a design element from human skin itself, a structure called the spinosum, which lies between the epidermis and dermis. They’re these little hill-like structures for sensing the direction a force is coming from.

BAO: If you add this hill-like structure, then depending on whether the force comes from left side or right side, because this dome or hill will be pressed from an angle, then only mechanoreceptor that’s on the opposite side of the direction of the force will be pressed and activated. This gives us a sense of direction of the shear force. 

CHEN: The hill structures are pretty small—a fraction of a millimeter in size—and she can pack them densely onto the electronic skin. But if you zoom in even further, you can see the other key structural design on their electronic skin. Bao’s group has fabricated tiny pyramids, tens of microns wide at the base.  

BAO: After a force is applied, these pyramids allow the elastic material to bounce back to its original shape once the force is removed.

CHEN: And in the future, Bao wants to borrow even more design elements from human physiology. She wants the sensors to pre-process some of the signal, like neurons do. 

BAO: This neural-like signal processing lets humans gather a large amount of information and train our brain to learn the patterns of information with very little consumption of energy.

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