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An implementation of a Physarum polycephalum model on a swarm of non-holonomic robots

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Abstract

The slime mold Physarum polycephalum is renowned for its incredible perceived intelligence despite it being a unicellular organism devoid of a central nervous system. Some notable abilities of the true slime mold include exploring an area for food sources and establishing energy-efficient networks between them. The network progression of the slime mold can be quantified as entropy of the system in combination with the nearest-neighbor distance of each plasmodium; specifically, as the network progresses we expect the entropy and average nearest-neighbor distance to decrease. The mold and its plasmodium explore an area using chemotaxis to move toward a higher concentration of a chemical stimulus within an extracellular chemical gradient. The slime mold’s chemotaxis behavior has been modeled using electrical networks, gradient fields, and nodal graphs. We leverage the use of a gradient field model to instruct individual agents, realized using simulated and real-world robots, within a multi-agent swarm to emulate the slime mold’s exploratory and network establishing behaviors. Beginning with a holonomic simulation and ending with a non-holonomic deployable protocol, the system’s entropy and distance to the nearest neighbor are compared between the two implementations. We demonstrate the efficacy of this model for use in multi-agent swarms, highlighting its ability to autonomously discover food sources (targets) while also establishing a network between them.

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Authors and Affiliations

  1. Georgia Institute of Technology, Atlanta, GA, USA

    Henry R. Chance

  2. U.S. Naval Research Laboratory, Washington, DC, USA

    Daniel M. Lofaro & Donald Sofge

Authors
  1. Henry R. Chance
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  2. Daniel M. Lofaro
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  3. Donald Sofge
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Correspondence to Henry R. Chance.

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This work was presented in part at the joint symposium of the 27th International Symposium on Artificial Life and Robotics, the 7th International Symposium on BioComplexity, and the 5th International Symposium on Swarm Behavior and Bio-Inspired Robotics (Online, January 25-27, 2022).

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Chance, H.R., Lofaro, D.M. & Sofge, D. An implementation of a Physarum polycephalum model on a swarm of non-holonomic robots. Artif Life Robotics 27, 663–673 (2022). https://doi.org/10.1007/s10015-022-00806-2

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  • DOI: https://doi.org/10.1007/s10015-022-00806-2

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