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PNAS Study Unveils 'Curvity' Rule to Steer Robot Swarms

The research treats collective motion as a materials-level effect set by an intrinsic curvature parameter.

Pictured above are robots, used in the Proceedings of the National Academy of Sciences study, that have the potential to advance "artificial swarm intelligence"—a type of AI that mimics flocking birds and schooling fish. Image courtesy of the Department of Artificial Intelligence, the Donders Center for Cognition, Radboud University. Photo Credit: Luco Buise.
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Overview

  • The paper, titled “A geometric condition for robot-swarm cohesion and cluster–flock transition,” was published September 8, 2025 in PNAS (DOI: 10.1073/pnas.2502211122).
  • The framework introduces an intrinsic property called curvity that governs whether self-propelled agents cluster, flock, or flow.
  • Laboratory tests showed the curvature-based rule controls attraction in robot pairs and scales to systems involving thousands of robots.
  • Curvity functions like a positive or negative charge and can be built into a robot’s mechanics to tune attraction or repulsion without centralized control.
  • Authors from New York University, Radboud University, and Tel Aviv University cite potential uses spanning industrial and delivery robots to microscopic drug-delivery devices.