Whoever said you can't teach an old dog or in this case plastic new tricks needs to reconsider that.
Researchers from Finland's Tampere University were able to train pieces of plastic to walk based on light.
Inspired by the conditioning process for dogs observed by Pavlov, the researchers used plastic made from synthetic temperature-responsive hydrogel containing plasmonic gold nanoparticles and merocyanine-based photoacid. But instead of getting it to move based on food, they used light.
Actuators can convert energy into movement
The plastics are soft actuators that are able to convert energy, in this case, light, into movement. The actuator first was only able to respond to heat but by associating light with heat, the plastic learned to respond to light as well.
According to researchers including senior author Arri Priimägi of Tampere University the plastic bends similar to how humans bend a finger. By illuminating the plastic intermittently, it walked, albeit slowly. The scientists said it moved at about the same pace that a snail does.
"We have designed a stimuli-driven actuator based on LCNs whose response is inspired by classical conditioning, one of the elementary forms of learning," the researchers wrote in journal Matter. "The actuator 'learns' to respond to an initially neutral stimulus (light) through an association process, which connects neutral stimulus (light) with an intrinsic stimulus (heat). Concrete potential for soft robotic applications is demonstrated by devising a walker and color-recognizing grippers that evolve to respond to light upon the association process, and modularity of the concept is further highlighted, curiously, by constructing an artificial Pavlov's dog."
Self-adapting robots up next?
The researchers noted that the actuator with an associative memory is much different than shape-memory materials and reconfigurable actuators because they respond to new, stimuli. something the conventional materials can't. It marks the first time a plastic object was trained to move without the need for a computer.
The scientists said they believe the responses and programmability of the actuators coupled with the ability to respond to diverse stimuli, could pave the way toward soft microrobotics that can learn and self adapt.