This paper presents a rotation-invariant embedded platform for simulating (neural) cellular automata (NCA) in modular robotic systems. Inspired by previous work on physical NCA, we introduce key innovations that overcome limitations in prior hardware designs. Our platform features a symmetric, modular structure, enabling seamless connections between cells regardless of orientation. Additionally, each cell is battery-powered, allowing it to operate independently and retain its state even when disconnected from the collective. To demonstrate the platform's applicability, we present a novel rotation-invariant NCA model for isotropic shape classification. The proposed system provides a robust foundation for exploring the physical realization of NCA, with potential applications in distributed robotic systems and self-organizing structures. Our implementation, including hardware, software code, a simulator, and a video, is openly shared at: https://github.com/dwoiwode/embedded_nca

翻译：本文提出了一种用于在模块化机器人系统中模拟（神经）元胞自动机的旋转不变嵌入式平台。受先前关于物理神经元胞自动机研究的启发，我们引入了关键创新，克服了先前硬件设计的局限性。我们的平台采用对称的模块化结构，使得元胞之间无论朝向如何都能实现无缝连接。此外，每个元胞由电池供电，使其能够独立运行，并在脱离集体时仍能保持其状态。为了展示该平台的适用性，我们提出了一种用于各向同性形状分类的新型旋转不变神经元胞自动机模型。所提出的系统为探索神经元胞自动机的物理实现提供了坚实的基础，在分布式机器人系统和自组织结构中具有潜在应用前景。我们的实现，包括硬件、软件代码、模拟器和视频，已在以下网址开源共享：https://github.com/dwoiwode/embedded_nca