Engineering researchers from the North Carolina State University and Temple University have developed new soft robots inspired by jellyfish. These jellyfish-shaped robots can outswim their real-life counterparts. The jellyfish robots portray a technique that uses pre-stressed polymers to make soft robots more robust and effective.

“Previous work by the researchers focused on making soft robots inspired by cheetahs. While those robots were super-efficient and fast, they lacked a bit with a stiff inner spine,” stated Jie Yin, the assistant professor of mechanical and aerospace engineering at NC State and corresponding author of a paper on the new research work. “We wanted to come up with a completely soft robot, which didn’t possess an inner spine and utilized that concept of switching between two new and stable states faster to make the soft robot move more powerfully. So, we choose jellyfish.”

Jellyfish Robots A Tiny Soft Robot

jellyfish robots, soft robotics, roft robot fish

Previous work by the team of researchers at North Carolina State University and Temple University focused on making soft robots inspired by cheetahs.

The researchers made the new soft robots from two super bonded layers of the same elastic polymer. One coat of polymer was pre-stressed or stretched and the second layer was not pre-stressed but contained in an air channel. “We can create the robot’ flex’ by pumping air into the layered channels, and we control the direction of that flex robot by controlling the relative thickness of the pre-stressed layer,” Yin stated.

Working mechanism of the jellyfish-inspired ‘soft robots’

When the body was combined with a third stress-free layer named the intermediate layer, the pre-stressed layer seeks to move in a particular direction. For example, one might get a piece of the polymeric strip that has been pre-stressed by pulling it together in two different directions.

After the pre-stressed material is attached to the intermediate layer, the result will be a bi-layer strip that would curve down, similar to a frowning face. If this bi-layer strip, also named the pre-stressed layer, is thinner than the outer layer with the air channel, that frowning curve will immediately bend into a smiling curve as the air pumps and goes into the channel layer. But, if the pre-stressed layer is thicker than the channel layer, the frown will become more prominent as air goes into the channel layer. In both ways, once the air leaves the channel layer, the material snaps back to its original ‘resting’ state.

This simple example describes the soft robots created by the researcher’s team. It resembles a larval insect curling in its body, then jumping forward as it goes on releasing its stored energy.

Soft Robots

The jellyfish-bot is, however, a bit more complicated, with the pre-stressed disk-like layer being stretched in four different directions. The channel layer is also separate and consists of a ring-like air channel. The result would be a dome that looks similar to a jellyfish. As the jellyfish-bot “relaxes,” the dome would curve up like a shallow bowl. When air is pumped into the channel layer, the dome immediately curves down, pushing out the water and propelling itself forward.

In experimental testing, the jellyfish-bot moved at an average speed of 53.3 millimetres per second. This is pretty efficient, considering that none of the three jellyfish species that the researchers examined went faster than an average rate of 30 millimetres per second.

The researchers ultimately came out with a three-pronged gripping robot, only with a twist. While most of the grippers hang open when “relaxed,” and need more energy to hold on to their cargo when lifted and moved, Yin and his colleagues used the pre-stressed layers to create useful grippers whose default position is clenched tightly shut.

The energy is required only to open the grippers, but once they form the position, the grippers return to their “resting” mode which is to hold the cargo tight. ‘The advantage here is that the robots don’t need any energy to hold on to the object during transport and hence is more efficient,’ Yin says.