In the vast, untamed depths of the ocean, tiny autonomous underwater vehicles (AUVs) are making waves, but not always in the way we’d like. These nautical mini-bots, while promising for ocean exploration and monitoring, often find themselves at the mercy of turbulent currents. But what if these currents could be harnessed, rather than fought against? That’s the question Caltech scientists, led by the ever-innovative John Dabiri, have been tackling.
Dabiri and his team have been working with an unlikely ally in their quest to conquer the ocean’s chaos: jellyfish. Outfitted with electronics and prosthetic “hats,” these bionic jellyfish can carry small payloads and report their findings back to the surface. But here’s the kicker—these brainless creatures don’t make decisions about navigation. Once deployed, they’re at the whim of the currents, with no remote control to guide them.
“We know that augmented jellyfish can be great ocean explorers, but they don’t have a brain,” Dabiri says. So, the team set out to develop a decision-making process for these underwater explorers. Enter CARL-Bot, the Caltech Autonomous Reinforcement Learning roBot, built by Dabiri’s former graduate student, Dr. Peter Gunnarson.
Gunnarson’s breakthrough came when he realized that the turbulent vortices created by ocean currents could be an advantage, not a hindrance, for smaller underwater vehicles. By using CARL-Bot’s single onboard accelerometer, Gunnarson could measure how the robot was being pushed around by vortex rings—underwater equivalents of smoke rings. The team then developed simple commands to help CARL detect a vortex ring’s relative location and position itself to “hop on and catch a ride basically for free,” as Gunnarson puts it. Alternatively, the bot can decide to avoid a vortex ring it doesn’t want to get pushed by.
This process, Dabiri points out, includes elements of biomimicry—taking a page from nature’s playbook. Birds and fish often take advantage of strong winds and currents to conserve energy. But in these natural cases, the systems use sophisticated sensory input and a brain to accomplish this. Dabiri hopes to marry this work with his hybrid jellyfish, using an onboard accelerometer to measure how the system is getting pushed around and demonstrating a similar capability to take advantage of environmental flows.
So, what does this mean for the future of ocean exploration? For starters, it could lead to more efficient and effective AUVs that can navigate the ocean’s chaotic fluid flow with ease. But it also raises questions about the role of biomimicry in underwater robotics. As we continue to push the boundaries of what’s possible in the deep sea, should we be looking to nature for inspiration? And if so, how far can we go before we cross the line from imitation to exploitation?
Moreover, this development challenges the norm of remote-controlled or AI-driven underwater vehicles. By harnessing the power of natural currents, these bots could operate more autonomously and efficiently, opening up new possibilities for ocean exploration and monitoring. But it also raises questions about the potential risks and ethical implications of deploying such autonomous systems in the ocean.
As we continue to grapple with these questions, one thing is clear: the future of ocean exploration is looking more and more like a dance with the currents. And who knows? Maybe one day, we’ll be sending jellyfish with prosthetic hats to explore the deepest trenches of the ocean. Stranger things have happened in the world of maritime innovation.