Autonomous odor source localization remains a challenging problem for aerial robots due to turbulent airflow, sparse and delayed sensory signals, and strict payload and compute constraints. While prior unmanned aerial vehicle (UAV)-based olfaction systems have demonstrated gas distribution mapping or reactive plume tracing, they rely on predefined coverage patterns, external infrastructure, or extensive sensing and coordination. In this work, we present a complete, open-source UAV system for online odor source localization using a minimal sensor suite. The system integrates custom olfaction hardware, onboard sensing, and a learning-based navigation policy trained in simulation and deployed on a real quadrotor. Through our minimal framework, the UAV is able to navigate directly toward an odor source without constructing an explicit gas distribution map or relying on external positioning systems. Vision is incorporated as an optional complementary modality to accelerate navigation under certain conditions. We validate the proposed system through real-world flight experiments in a large indoor environment using an ethanol source, demonstrating consistent source-finding behavior under realistic airflow conditions. The primary contribution of this work is a reproducible system and methodological framework for UAV-based olfactory navigation and source finding under minimal sensing assumptions. We elaborate on our hardware design and open source our UAV firmware, simulation code, olfaction-vision dataset, and circuit board to the community. Code, data, and designs will be made available at https://github.com/KordelFranceTech/ChasingGhosts.

翻译：自主气味源定位对于空中机器人而言仍是一个具有挑战性的问题，这主要源于湍流、稀疏且延迟的感官信号，以及严格的载荷和计算限制。尽管先前基于无人机（UAV）的嗅觉系统已展示了气体分布图构建或反应式羽流追踪能力，但它们依赖于预定义的覆盖模式、外部基础设施或大量的传感与协调。在本工作中，我们提出了一套完整、开源的无人机系统，用于使用最小化传感器套件实现在线气味源定位。该系统集成了定制的嗅觉硬件、机载传感，以及一个在仿真环境中训练并部署于真实四旋翼飞行器上的基于学习的导航策略。通过我们的最小化框架，无人机能够直接导航至气味源，而无需构建显式气体分布图或依赖外部定位系统。视觉作为一种可选补充模态被引入，以在特定条件下加速导航。我们通过在大型室内环境中使用乙醇源进行的真实飞行实验验证了所提出的系统，展示了其在真实气流条件下一致的气味源寻找行为。本工作的主要贡献在于，在最小化传感假设下，为基于无人机的嗅觉导航与气味源寻找提供了一套可复现的系统和方法论框架。我们详细阐述了硬件设计，并向社区开源了无人机固件、仿真代码、嗅觉-视觉数据集以及电路板。代码、数据和设计将在 https://github.com/KordelFranceTech/ChasingGhosts 上提供。