They have no control technology, no batteries: Researchers have developed simple and innovative soft robots that can only navigate complex environments using their so-called physical intelligence and energy from the environment. Spirelli noodle-like structures made of a twisted strip of liquid crystalline elastomer move in a directed fashion on warm surfaces and can wriggle out of labyrinths. Scientists say the principle could be useful in developing new concepts in robotics.
They must be able to handle special environmental challenges and complete tasks independently: Research teams around the world are currently working on robots with many different characteristics and in different fields of application. A special section called soft robotics: instead of hard structures, developers use soft materials to produce robots with “soft” and flexible properties. They are usually controlled by humans or by electronics based on integrated data processing.
Material and structure instead of complex technology
But the navigation capabilities of the soft robots, being provided by researchers led by Jie Yin of North Carolina State University, do not depend on external guidance or integrated software. Our designs illustrate a concept called physical intelligence. This means that the structure and smart materials allow robots to navigate different situations, unlike computational intelligence,” explains Yin. The concept behind their development seems correspondingly simple: their soft robots are twisted ribbons made of a liquid crystal rubber material that resembles transparent Spirelli noodles.
The secret of its mobility lies in the strong reactions of plastics to temperature differences: if you place a structure on a surface with a temperature of at least 55 ° C, the parts of the twisted tape that touch the surface shrink due to heat. Elevated parts exposed only to cold air remain unchanged. Scientists explain that these processes trigger dynamics that lead to a directed rolling motion of the structure. The warmer the surface, the faster the robot will move forward. “Similar objects were shown for smooth-sided sticks, but this simple shape had the disadvantage that the object rotates in place when it encounters an obstacle,” Yin says. “The soft robot that we made in the form of a twisty bar, on the other hand, is able to avoid such obstacles without human or computer intervention.”
Clever ‘brainless’ on the go
According to the researchers, the “Spirelli robot” achieves this in two ways: when part of the structure encounters an object, it can rotate sideways to move around the obstacle. Second, there is a kind of snap effect when the middle part of the robot hits an object. By continuing to move with the partial occlusion, deformation energy accumulates, which can then be suddenly discharged. This causes the robot to jump a bit, which also allows for a new orientation. This way, he can finally get back on the right track and continue his way through an obstacle course.
Scientists used various experiments to show what the concept could achieve. So the robots were able to move on different structural surfaces – including granular surfaces. They even managed to overcome sandy obstacles with a slope of up to 15 degrees. Material intelligence was particularly evident when used in labyrinth systems: simple structures could only find their way to the exit unaided thanks to materials and structural design. “The principle is similar to the autonomous vacuum cleaner robots that many people use in the home,” says Yin. “Only this soft robot we have developed derives its energy from its environment and does not require computer programming.”
As the team concluded, the concept is more than just a weird gimmick: “The system is fun and interesting, but more importantly it offers new insights into how to design soft robots that are able to absorb heat energy from natural environments and move autonomously in complex and unstructured environments such as Harsh roads and deserts.” Yin says.
Source: North Carolina State University, professional article: Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.2200265119
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