Stanford researchers have reportedly developed a new vine-like, growing robot. This robot could become particularly useful for rescue operations as well as medical applications.

The Robot

Stanford researchers have reportedly developed a new vine-like robot, which can “grow across long distances without moving its whole body.” The mechanical engineers issued a detailed report on June 19th describing their creation. The robot was reportedly inspired by existing organisms in nature, which manage to grow across wide distances, such as vines, nerve cells and fungi.

The researchers created a prototype for the robot, made of a soft material, and tested its ability to travel through different obstacles towards a particular goal. Some of the obstacles the researchers made it face include flypaper, nails, sticky glue as well as an ice wall. Its goal was to deliver a carbon dioxide sensor.

The robot could obviously have a wide variety of practical applications, including being used as part of a search and rescue team, in order to help save people from the rubble of a fallen building, for example. The carbon dioxide sensor in the researchers’ experiments could be used to detect carbon dioxide emitted from trapped survivors. It can also be programmed to be used for medical applications.

Researchers On the Robot

“Essentially, we’re trying to understand the fundamentals of this new approach to getting mobility or movement out of a mechanism,” explained the lead author and mechanical engineering professor, Allison Okamura. “It’s very, very different from the way that animals or people get around the world.”

“The body lengthens as the material extends from the end but the rest of the body doesn’t move,” said Elliot Hawkes, an assistant professor from California University. “The body can be stuck to the environment or jammed between rocks, but that doesn’t stop the robot because the tip can continue to progress as new material is added to the end.”

Co-author, Joey Greer, said: “Also, using a camera to guide the robot to a target is a difficult problem because the camera imagery needs to be processed at the rate it is produced. A lot of work went into designing algorithms that both ran fast and produced results that were accurate enough for controlling the soft robot.”

“The applications we’re focusing on are those where the robot moves through a difficult environment, where the features are unpredictable and there are unknown spaces,” said Laura Blumenschein, a graduate student in the Okamura lab and co-author of the paper. “If you can put a robot in these environments and it’s unaffected by the obstacles while it’s moving, you don’t need to worry about it getting damaged or stuck as it explores.”

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