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Robotic Hand Outfitted with Adhesive Based on Gecko Toes

Robotic Hand Outfitted with Adhesive Based on Gecko Toes

from hackster.io

Engineers from Stanford University’s Biomimetics and Dexterous Manipulation Lab have developed a robotic gripper with adhesives inspired by geckos that allow it to pick up everything from fresh eggs to basketballs. Typically, robotic grippers can either manipulate delicate objects, such as tomatoes, or heavy objects like bricks. The new robotic gripper can be both dexterous and robust simultaneously.



The gripper, known as farmHand, was designed using two forms of biological inspiration – multijointed fingers, like those oh humans, and gecko-inspired adhesives. The grippy but not sticky adhesives are based on the structures of gecko toes, which have been in development over the last decade.

The adhesive provides a strong hold via microscopic flaps like its biological counterpart. When in contact with a surface, the flaps create a Van der Waals force. This weak intermolecular force results from subtle differences in the positions of electrons on the outsides of molecules. This results in adhesives that can grip firmly but require little actual force. What’s more, they don’t feel sticky to the touch or leave a residue behind.

While the gecko-like flaps can grip smooth surfaces, it has to do so in a certain way to elicit that Van der Waals force. This is easy enough to achieve on smooth flat surfaces but difficult when gripping objects at various angles.

To overcome the issue, the team designed a pad that sits below the adhesive and features a collapsible rib structure that buckles with little force. When in contact with an object, no matter the angle, the ribs buckle, providing equal force on the adhesive and preventing any slippage.

The gripper’s artificial tendons also play a role, as they provide a hyperextended pinch in a ‘C-like’ shape with the tips of the fingers, which gives the adhesive more surface area when grasping objects. The researchers are now looking at ways to provide feedback features to better understand how it could grip more efficiently while the hand is in use.

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