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Robots assemble complex shapes using neural cellular automata

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework for distributed swarm morphogenesis, enabling robots to autonomously assemble into desired shapes. This system integrates neural cellular automata (NCA) with site selection and collision-aware control, introducing a decentralized mechanism for robots to identify new attachment sites based on local NCA states. The method includes offline sparse-retention fine-tuning to better match NCA growth with physical assembly, demonstrating successful formation of diverse lattice morphologies with hundreds of robots and improved accuracy. Experiments with Crazyflie quadrotors validated the pipeline using robot-relative observations. AI

IMPACT Enables more complex autonomous coordination in multi-robot systems, potentially impacting construction and exploration.

RANK_REASON Academic paper detailing a novel method for multi-robot coordination using neural cellular automata. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Robots assemble complex shapes using neural cellular automata

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Academic paper detailing a novel method for multi-robot coordination using neural cellular automata. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Anthony Tzes ·

    Distributed Swarm Morphogenesis with Neural Cellular Automata

    Swarm morphogenesis requires robots to assemble desired shapes through local interactions. We present a modular framework integrating neural cellular automata (NCA) with existing site selection and collision-aware control. Within this framework, we introduce a decentralized attac…

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