发表机构
EssilorLuxottica; Politecnico di Milano（依视路陆逊梯卡集团; 米兰理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
介绍ARGO智能眼镜平台，通过硬件、固件和人工智能整体协同设计，利用STM32N6微控制器及集成神经处理单元实现设备端机器学习，以优化的YOLOv11模型识别障碍物，展示了高性能、隐私保护辅助设备可行性。
AI 中文摘要
本文介绍了ARGO智能眼镜平台，旨在兼顾人体工程学舒适度、高计算吞吐量和能源效率。与依赖云的解决方案不同，ARGO利用STM32N6微控制器及其集成神经处理单元实现设备端机器学习，通过本地数据处理减少延迟并保护用户隐私。主要贡献在于硬件、固件和人工智能的整体协同设计，以优化的YOLOv11模型进行实时城市障碍物识别。为确保与目标NPU兼容，引入头部并行注意力（HPA）。模型在WOTR数据集上训练，最终配置在严格内存限制下mAP50 - 95为24，内存占用仅2.483MB。平台集成多模态传感器套件，200mAh电池下续航约113分钟，帧率10FPS。这些结果证明了高性能、隐私保护且社会可接受的辅助设备的可行性，凸显了竞争优势的人工智能解决方案对紧密集成、多学科协同设计方法的需求。
英文摘要
This paper presents ARGO, a smart eyewear platform designed to bridge ergonomic comfort, high computational throughput, and energy efficiency. Unlike cloud-dependent solutions, ARGO leverages the STM32N6 microcontroller and its integrated Neural Processing Unit (NPU) to enable on-device machine learning, minimizing latency and preserving user privacy through local data processing. The primary contribution lies in the holistic co-design of hardware, firmware, and artificial intelligence, centered on the deployment of an optimized YOLOv11 model for real-time urban obstacle recognition. To ensure compatibility with the target NPU, we introduce Head-wise Parallel Attention (HPA), an architectural refinement that enables efficient accelerator execution while preserving the original computational logic. The model is trained on the Walking On The Road (WOTR) dataset, and the final deployed configuration achieves an mAP50-95 of 24 under strict memory constraints, with a memory footprint of only 2.483 MB. The platform integrates a multimodal sensor suite, RGB cameras, Time-of-Flight sensors, microphones, and ambient sensors, and delivers 10 FPS at a continuous autonomy of ~113 minutes on a 200 mAh battery. These results demonstrate the feasibility of a high-performance, privacy-preserving, and socially acceptable assistive device, and highlight how competitive edge AI solutions increasingly demand tightly integrated, multidisciplinary co-design approaches.
CommentsThis work was carried out in the EssilorLuxottica "Smart Eyewear Lab", a Joint Research Center between EssilorLuxottica and Politecnico di Milano
