MSGID: 1:317/3 648007f4   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    Swarming microrobots self-organize into diverse patterns    
      
     Date:   
         June 6, 2023   
     Source:   
         Cornell University   
     Summary:   
         A research collaboration between Cornell and the Max Planck   
         Institute for Intelligent Systems has found an efficient way   
         to expand the collective behavior of swarming microrobots:   
         Mixing different sizes of the micron- scale 'bots enables them to   
         self-organize into diverse patterns that can be manipulated when a   
         magnetic field is applied. The technique even allows the swarm to   
         'cage' passive objects and then expel them.   
      
      
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   FULL STORY   
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   A research collaboration between Cornell and the Max Planck Institute for   
   Intelligent Systems has found an efficient way to expand the collective   
   behavior of swarming microrobots: Mixing different sizes of the   
   micron-scale 'bots enables them to self-organize into diverse patterns   
   that can be manipulated when a magnetic field is applied. The 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, "Programmable Self-Organization of Heterogeneous   
   Microrobot Collectives," published June 5 in Proceedings of the National   
   Academy of Sciences.   
      
   The lead author is Steven Ceron, Ph.D. '22, who worked in the lab of   
   the paper's co-senior author, Kirstin Petersen, 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 -- from algorithms and classical control to   
   physical intelligence -- to coax large robot collectives into behaving   
   intelligently, often by leveraging the robots' interactions with their   
   environment and each other. 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.   
      
   "The difficulty is how to enable useful behaviors in a swarm of robots   
   that have no means of computation, sensing or communication," Petersen   
   said. "In our last paper, we showed that by using a single global signal   
   we could actuate robots, in turn affecting their pairwise interactions to   
   produce collective motion, contact- and non-contact-based manipulation   
   of objects. Now we have shown that we can expand that repertoire of   
   behaviors even further, simply by using different sizes of microrobots   
   together, such that their pairwise interactions become asymmetric."   
   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.   
      
   "By changing the global magnetic field, we can change the relative   
   magnitudes of those forces, " Petersen said. "And that changes the   
   overall behavior of the swarm."  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 reason why we're always excited when the systems are capable   
   of caging and expulsion is that you could, for example, drink a vial   
   with little microrobots that are completely inert to your human body,   
   have them cage and transport medicine, and then bring it to the right   
   point in your body and release it," Petersen said. "It's not perfect   
   manipulation of objects, but in the behaviors of these microscale   
   systems we're 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.   
      
   "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," said   
   Ceron, currently a postdoctoral fellow at Massachusetts Institute of   
   Technology. "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."  The research   
   was supported by the Max Planck Society, the National Science Foundation,   
   the Fulbright Germany Scholarship and the Packard Foundation Fellowship   
   for Science and Engineering.   
      
       * RELATED_TOPICS   
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             o Octopus o Bioinformatics o Nanorobotics o Autism o   
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   ==========================================================================   
   Story Source: Materials provided by Cornell_University. Original written   
   by David Nutt, courtesy of the Cornell Chronicle. Note: Content may be   
   edited for style and length.   
      
      
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   Journal Reference:   
      1. Steven Ceron, Gaurav Gardi, Kirstin Petersen, Metin   
      Sitti. Programmable   
         self-organization of heterogeneous microrobot   
         collectives. Proceedings of the National Academy of Sciences,   
         2023; 120 (24) DOI: 10.1073/ pnas.2221913120   
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   Link to news story:   
   https://www.sciencedaily.com/releases/2023/06/230606111700.htm   
      
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