Though autonomy in robotics constructed of soft materials is essential, creating autonomous soft robots that can intelligently interact with and adapt to changing environments without external controls remains challenging. Such robots usually require a soft, brainlike command center that integrates on-board sensing, control, computation, and decision-making.
In a paper published in the Proceedings of the National Academy of Sciences, researchers from Penn and North Carolina State University have developed soft robots that are capable of navigating complex environments, such as mazes, without input from humans or computer software. Shu Yang, Joseph Bordogna Professor and chair of the Department Materials Science and Engineering, co-authored the paper.
Yang is an expert on the properties of liquid crystal elastomers, the material the the soft robots are made of. Thanks to those properties and their shape—a twisted ribbon resembling translucent rotini—the robots demonstrate a concept called “physical intelligence:” structural design and smart materials are what allow the soft robot to navigate various situations, rather than computational intelligence.
When placed on a surface that is at least 55° Celsius (131° Fahrenheit), which is hotter than the ambient air, the portion of the ribbon touching the surface contracts, while the portion of the ribbon exposed to the air does not. This induces a rolling motion in the ribbon. The warmer the surface, the faster it rolls.
“I noticed the snapping behaviors,” Yang says, “which are different from the typical twisting and untwisting behaviors that are due to the shrinkage of the material. If the helices only twist and untwist, they wouldn’t be able to bounce and move, but this snapping provides elastic energy to the helix when in contact with an obstacle, allowing it to bounce and become ‘autonomous.’”
The robot’s ability to navigate mazelike environments highlights the seemingly endless opportunities to utilize it in complex, unstructured settings such as roads and harsh deserts, which can include harvesting heat energy from natural environments
This story is by Ebonee Johnson. Read more at Penn Engineering Today.