Our robot is inspired by the common moon jellyfish. Willyam Bradberry/Shutterstock
Some of the last areas of pristine and untouched wilderness on Earth exist beneath the seas. Yet these marine ecosystems are under threat from deep-sea mining projects, oil rigs and offshore windfarms. When these facilities are built and maintained, they tend to damage the rich ecological networks around them.
Roboticists and engineers are working to address this problem, searching for new ways to create machines that might help repair, maintain or inspect the undersea components of the growing offshore industry. Led by colleagues Thierry Bujard and Gabriel Weymouth from the University of Southampton, my team has found a solution to this problem, designing underwater robots inspired by nature’s smartest swimmers: the ultra-efficient moon jellyfish.
Traditional aquatic robots are designed for two main purposes: for efficient, long-distance navigation across open stretches of water, and for tasks requiring high manoeuvrability close to submerged structures. Both types of robot are effective, but few robots combine efficient travel with high manoeuvrability. That means most aquatic robots are too clumsy and clunky to support the offshore industry without also harming the undersea environment.
Indeed, with the expansion of offshore developments to increasingly fragile environments, even state-of-the-art marine robots are struggling to cope with the complexity of their missions. Lots of research is currently going into developing autonomous deep sea robots, with initiatives like Xprize offering funding to some of the most exciting ideas.
To respond to these challenges, engineers have looked to biology to inspire new forms of robotic underwater propulsion. After millions of years of evolution, the logic goes, aquatic creatures should offer models to help address the weaknesses of the current crop of underwater robots.
The swimming mode of fish, based on the flapping of their different fins, has become the primary source of inspiration for those experimenting with new underwater vehicles. But the pulse-jet swimming mode favoured by jellyfish is widely regarded as the world’s most efficient underwater propulsion mechanism, offering a more compelling technological solution that’s far easier for roboticists to imitate.
Pulse-jetting relies on the cyclic expansion and contraction of a hollow cavity of the specimen’s body. This system drives the ingestion and expulsion of water, which ultimately provides jellyfish with a form of propulsion.
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Despite its simplicity, this swimming strategy can result in incredible agility as well as being highly energy efficient. The fastest squid can travel up to 8 metres per second using a pulse-jet system, while the jellyfish Aurelia aurita (also known as the moon jellyfish) is known to be the most efficient swimmer on the planet.
By copying these organisms when we build underwater robots, we can design new underwater vehicles capable of combining high manoeuvrability with unmatched efficiency. In our recent research, we developed a new bio-inspired robot that can match the propulsive efficiency of the Aurelia aurita. To do this, we mimicked the key principle that enables jellyfish to achieve their high propulsive efficiency: resonance.
Resonance is a physical phenomenon commonly encountered in many everyday activities such as walking, playing on a swing and even singing. If we watch a swinging pendulum, for example, we know from experience that it will continue oscillating until it comes to rest, hanging in a vertical position as determined by gravity. The frequency with which the pendulum oscillates is referred to as its “natural frequency”.
From experience, we also know that if we want to keep the pendulum oscillating, the easiest way to do this is by giving it a helpful nudge every time it reaches the highest point of its oscillation, just as we do when we push a child higher on a swing. When we do this, we are allowing the pendulum or swing to “resonate”.
So, resonance occurs when an external force affects a system at its natural frequency, causing the system to achieve larger amplitude oscillations at a fraction of the force needed. That’s what makes operating at resonance so efficient. We applied the same principle to the propulsion of our jellyfish-inspired robot.
We hypothesised that by designing a robot jellyfish with an elastic propulsive system, we could exploit the inherent natural frequency of that elastic to drive the mechanism into resonance. In resonance, our robot would issue powerful pulsed jets at a fraction of the energy cost.
The robot we developed has an elastic inner chamber, which expands and collapses under the effect of an umbrella-like mechanism. When tested in a water tank, the robot was found to increase its swimming speed as the speed at which it pulsed approached the natural frequency of the robot jellyfish’s elastic chamber. It proved that our robot jellyfish had achieved resonance.
The efficiency of a system that propels itself, be it mechanical or biological, is based on an equation that combines the power absorbed, the speed of the system and its mass. When applied to our robot, that equation put our robot jellyfish on par with the Aurelia aurita jellyfish.
This is a striking result with a twofold impact. On one hand, it shows for the first time that a mechanical system can achieve the propulsive efficiency of the best of nature’s swimmers. On the other hand, our robot has explained the outstanding swimming of its biological counterparts – which may now help biologists return to the study of jellyfish and squid with an entirely new perspective.
Powered by a system inspired by the most efficient of nature’s swimmers, our robot jellyfish provides a prototype of a dynamic and efficient underwater robot, which the offshore windfarm industry may one day use to maintain the parts of their infrastructure that lie beneath the waves.
About the Authors
Francesco Giorgio-Serchi, Chancellor's Fellow in Robotics and Autonomous Systems, University of Edinburgh
This article was updated on February 24 2021 to credit the team from the University of Southampton who also worked on this research.
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