Distributed Swarm Morphogenesis with Neural Cellular Automata

Computer Science > Robotics

[Submitted on 22 Oct 2026 (v1), last revised 26 Oct 2026 (this version, v2)]

Title:Distributed Swarm Morphogenesis with Neural Cellular Automata

View PDF HTML (experimental)Abstract:Swarm morphogenesis requires robots to assemble desired shapes through local interactions. We present a modular framework integrating neural cellular automata (NCA) with existing site assignment and collision-aware control. Within this framework, we introduce a decentralized attachment-site discovery mechanism. Robots already in the formation update and share local NCA states to identify new attachment sites, enabling progressive growth without a predefined list of sites during deployment. To bridge the mismatch between conventional NCA growth and gradual physical assembly, we additionally propose offline sparse-retention fine-tuning that simulates partial attachment, together with a false-positive loss that penalizes invalid site activations. Simulations demonstrate formation of diverse lattice morphologies, scaling to several hundred robots, and substantial improvements in morphology accuracy from the proposed fine-tuning. Experiments with Crazyflie quadrotors validate the integrated execution pipeline using robot-relative observations reconstructed from external tracking.

Submission history

From: Ray Verma [view email][v1] Thu, 22 Oct 2026 20:52:51 UTC (1,138 KB)

[v2] Mon, 26 Oct 2026 14:29:57 UTC (1,139 KB)

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