A team of researchers from Cornell University and the Max Planck Institute for Intelligent Systems has developed a new technique for swarming microrobots. The team found that mixing different sizes of the micron-scale robots enabled them to self-organize into diverse patterns that can be manipulated with a magnetic field. The new technique even allows the swarm to “cage” passive objects and then expel them. The approach may help inform how future microrobots could perform targeted drug release in which batches of microrobots transport and release a pharmaceutical product in the human body.
The team’s paper, titled “Programmable Self-Organization of Heterogeneous Microrobot Collectives,” was published on June 5 in Proceedings of the National Academy of Sciences. The lead author is Steven Ceron, who worked in the lab of the paper’s co-senior author, Kirstin Petersen, an assistant professor and an Aref and Manon Lahham Faculty Fellow in the Department of Electrical and Computer Engineering in Cornell Engineering.
Petersen’s Collective Embodied Intelligence Lab has been studying a range of methods to coax large robot collectives into behaving intelligently. However, this approach is exceedingly difficult when applied to microscale technologies, which aren’t big enough to accommodate onboard computation.
To tackle this challenge, Ceron and Petersen teamed up with the paper’s co-authors, Gaurav Gardi and Metin Sitti, from the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. Gardi and Sitti specialize in developing microscale systems that are driven by magnetic fields.
By using microrobots of varying size, the researchers demonstrated they could control the swarm’s level of self-organization and how the microrobots assembled, dispersed, and moved. The researchers were able to change the overall shape of the swarm from circular to elliptical, force similarly sized microrobots to cluster together into subgroups, and adjust the spacing between individual microrobots so that the swarm could collectively capture and expel external objects.
The microrobots in this case are 3D-printed polymer discs, each roughly the width of a human hair, that have been sputter-coated with a thin layer of a ferromagnetic material and set in a 1.5-centimeter-wide pool of water. The researchers applied two orthogonal external oscillating magnetic fields and adjusted their amplitude and frequency, causing each microrobot to spin on its center axis and generate its own flows. This movement in turn produced a series of magnetic, hydrodynamic, and capillary forces.
Petersen said, “By changing the global magnetic field, we can change the relative magnitudes of those forces, and that changes the overall behavior of the swarm.”
The reason why the researchers are excited about the system’s capability of caging and expulsion is that in the future, microrobots could be used to transport medicine into the human body. A vial of microrobots that is inert to the human body could be introduced, and then the microrobots could cage and transport medicine to the right point in the body and release it. In the behaviors of these microscale systems, the researchers are starting to see a lot of parallels to more sophisticated robots despite their lack of computation, which is pretty exciting.
Ceron and Petersen used a swarming oscillator model—or swarmalator—to characterize precisely how the asymmetric interactions between different-sized disks enabled their self-organization. Now that the team has shown that the swarmalator fits such a complex system, they hope the model can also be used to predict new and previously unseen swarming behaviors.
Ceron said, “With the swarmalator model, we can abstract away the physical interactions and summarize them as phase interactions between swarming oscillators, which means we can apply this model, or similar ones, to characterize the behaviors in diverse microrobot swarms. Now we can develop and study magnetic microrobot collective behaviors and possibly use the swarmalator model to predict behaviors that will be possible through future designs of these microrobots.”
“In the current study, we were programming differences between exerted forces through the microrobots’ size, but we still have a large parameter space to explore,” he said. “I’m hoping this represents the first in a long line of studies in which we exploit heterogeneity in the microrobots’ morphology to elicit more complex collective behaviors.”
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