In an innovative study published in Nature Communications, a research team led by Dai Owaki, an associate professor in the Department of Robotics at Tohoku University’s Graduate School of Engineering, used moderate electric pulses to successfully regulate jellyfish's swimming behavior. They used a lightweight artificial intelligence (AI) model to forecast each jellyfish’s swimming speed.
Motion prediction with jellyfish hybrid reservoir computing system. Image Credit: Dai Owaki
Jellyfish, unlike fish, have no bones and only a rudimentary nerve net, yet they can travel long distances with little energy cost. A jellyfish’s seemingly smooth glide through the water is due to a ring of muscle within its soft belly, which generates a simple jet that propels it ahead. Scientists call this fundamental potential “embodied intelligence,” implying that the organism’s physical structure contributes to problem solving.
When harnessed, this movement effectively monitors coral reefs, traces oil spills, and observes climate change. “Jellyfish cyborgs” use little power and run without engines, reducing the environmental impact of present ways of exploring the huge ocean.
The findings demonstrate the collaborative capability of soft-bodied marine animals with simple electronic systems in aquatic environments, all while maintaining the animal’s natural swimming style.
Our research team posed two interconnected questions. First, can we identify a pulse pattern that the jellyfish accepts, enabling it to swim at predetermined speeds without undue stress? Second, once the jellyfish responds to these signals, can we develop a compact AI tool capable of predicting its movement in any direction? By addressing these inquiries, we can pave the way for low-energy, environmentally friendly oceanic probes.
Dai Owaki, Associate Professor, Department of Robotics, Tohoku University
Owaki's team consisted of Max Austin, an assistant professor, and Kohei Nakajima, an associate professor, both from the Department of Mechano-Informatics at The University of Tokyo’s Graduate School of Information Science and Technology, as well as Shuhei Ikeda and Kazuya Okuizumi from the Kamo Aquarium in Tsuruoka City, Yamagata Prefecture.
The team used small electrodes on the jellyfish’s muscle ring to give short electric pulses every 1.5 to 2 seconds. Each swimming event was captured with a single camera and two mirrors, and the entire three-dimensional route was reconstructed on a laptop. The most efficient pulse timing corresponded to the jellyfish’s natural rhythm, resulting in increased swimming speed.
The data was then fed into a lightweight hybrid “physical reservoir” AI model, which includes the jellyfish’s body as a key component of the computing system. The model predicted future speeds with sufficient accuracy in all transverse directions.
Owaki added, “We were intrigued to discover that the most effective control signals were not the rapid pulses, but rather those that mirrored the jellyfish's natural rhythm. Attempts to use stronger or faster pulses led to decreased swimming efficiency and erratic movement, underscoring the importance of aligning with the rhythms of nature, rather than opposing them.”
The concept of a living organism operating as a computational device may sound like science fiction, yet it has the potential to transform many fields. Soft-bodied organisms may inspire advancements in robotic systems with self-healing and flexible qualities.
Fleets of cyborg jellyfish may explore the waters for extended periods of time, measuring temperature, salinity, and plastic pollution without relying on batteries. The study combines marine science and engineering by creating a unique, gentle cyborg swimmer.
Jellyfish were chosen for this study because they have the highest swimming efficiency among marine species, making them a suitable model for investigating the synergy between biological systems and simple hardware. Seeing these exquisite creatures glide across the water inspired the research team to create technology that works with, rather than against, natural ecosystems.
Journal Reference:
Owaki, D., et al. (2025) Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs. Nature Communications. doi.org/10.1038/s41467-025-59889-7.