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Combined Strength of Six Ant-Inspired Microrobots Can Move a Two-Ton Car

ByAllison EckNOVA NextNOVA Next

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Scientists have invented a mini-robot that can move objects over 2,000 times its own weight.

And that’s not even its most impressive credential. Together with five of its comrades, this tiny robot can pull a car weighing nearly 4,000 pounds.

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The researchers who developed the technology at the Biomimetics and Dexterous Manipulation Laboratory at Stanford University say that their robot team works cooperatively through the smooth synchronization of tiny forces. For best results, each microrobot moves three of its six legs simultaneously. That strategy is modeled after ants, whose neck joints—according to a 2014 study in the Journal of Biomechanics—can withstand loads of about 5,000 times their body weight. Together, ants can lift objects much heavier than own collective weight.

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Ant swarm behavior, which allows teams of ants to forage massive pieces of food, inspired the Stanford team’s powerful microrobots.

Here’s John Markoff, reporting for The New York Times:

“By considering the dynamics of the team, not just the individual, we are able to build a team of our ‘microTug’ robots that, like ants, are superstrong individually, but then also work together as a team,” said David Christensen, a graduate student who is one of the authors of a research paper describing the feat. The paper will be presented this May at the International Conference on Robotics and Automation in Stockholm.

Their new demonstration is the functional equivalent of a team of six humans moving a weight equivalent to that of an Eiffel Tower and three Statues of Liberty, Mr. Christensen said. The car is the one he uses for commuting to campus.

Scientists are studying ants to find more creative ways to get small robots to accomplish big tasks.

The robots also employ a special adhesive that mimics gecko toes—another trait that has led to many innovations throughout the short but rich history of bioinspired robots . The team’s statistical model showing how weights can be efficiently distributed among groups of participants could change the way engineers think about bioinspired tech in much the same way that parallel computing—where multiple processors work on chunks of the same data—changed the way computer scientists approached artificial intelligence.