基于嗅觉仿生的具身智能警犬设计研究

Research on Embodied Intelligent Police Dog Design Based on Olfactory Bionics

摘要: 随着公共安全需求升级，复杂非结构化场景对嗅探装备的持久性、精准性要求显著提升，并在一定程度上替代活体警犬进行爆炸物探测、毒品查缉等警务活动，解决其训练周期长、成本高、环境适应性弱等局限。通过融合仿生嗅觉传感、气体扩散建模与机器人技术，设计基于嗅觉仿生的具身智能警犬系统，分析犬类嗅觉受体分布与气味分子吸附机制，研发纳米材料修饰的高灵敏仿生嗅觉传感器阵列，构建融合深度学习与流体力学模型的多模态识别算法，实现痕量气体检测与气味源定位，结合四足机器人平台，开发动态采样与路径规划技术，解决非结构化地形追踪难题，为公安工作研制“嗅觉侦查”警用装备，提供借鉴参考。

Abstract: With the escalation of public security demands, complex unstructured scenarios have significantly raised requirements for the durability and precision of sniffing equipment. Such equipment is increasingly replacing live police dogs in law enforcement activities such as explosive detection and drug interdiction, addressing limitations including long training cycles, high costs, and weak environmental adaptability. By integrating bionic olfactory sensing, gas diffusion modeling, and robotics technology, this study designs an embodied intelligent police dog system based on olfactory bionics. It analyzes the distribution of canine olfactory receptors and the mechanisms of odor molecule adsorption to develop a high-sensitivity bionic olfactory sensor array modified with nanomaterials. Furthermore, it constructs a multimodal recognition algorithm fusing deep learning with fluid dynamics models to achieve trace gas detection and odor source localization. Combined with a quadruped robot platform, the project develops dynamic sampling and path planning technologies to solve tracking challenges in unstructured terrains. Ultimately, this research aims to develop “olfactory reconnaissance” police equipment for public security operations, providing a valuable reference for future applications.