The Sterile Processing and Distribution (SPD) department is responsible for cleaning, disinfecting, inspecting, and assembling surgical instruments between surgeries. Manual inspection and preparation of instrument trays is a time-consuming, error-prone task, often prone to contamination and instrument breakage. In this work, we present a fully automated robotic system that sorts and structurally packs surgical instruments into sterile trays, focusing on automation of the SPD assembly stage. A custom dataset comprising 31 surgical instruments and 6,975 annotated images was collected to train a hybrid perception pipeline using YOLO12 for detection and a cascaded ResNet-based model for fine-grained classification. The system integrates a calibrated vision module, a 6-DOF Staubli TX2-60L robotic arm with a custom dual electromagnetic gripper, and a rule-based packing algorithm that reduces instrument collisions during transport. The packing framework uses 3D printed dividers and holders to physically isolate instruments, reducing collision and friction during transport. Experimental evaluations show high perception accuracy and statistically significant reduction in tool-to-tool collisions compared to human-assembled trays. This work serves as the scalable first step toward automating SPD workflows, improving safety, and consistency of surgical preparation while reducing SPD processing times.

翻译：无菌处理与分发部门负责在手术间隙对手术器械进行清洁、消毒、检查和组装。器械托盘的手动检查与准备工作耗时、易错，且常易发生污染和器械损坏。本研究提出了一套全自动机器人系统，用于分拣手术器械并将其结构化地装入无菌托盘，重点关注SPD组装阶段的自动化。我们收集了一个包含31种手术器械和6,975张标注图像的自定义数据集，用于训练混合感知流程：采用YOLO12进行检测，并采用基于级联ResNet的模型进行细粒度分类。该系统集成了标定视觉模块、配备定制双电磁夹爪的6自由度史陶比尔TX2-60L机械臂，以及基于规则的装箱算法以减少器械在运输过程中的碰撞。装箱框架采用3D打印的分隔片和固定器对器械进行物理隔离，从而降低运输过程中的碰撞与摩擦。实验评估表明，该系统具有较高的感知精度，且与人组装的托盘相比，器械间碰撞在统计上显著减少。本工作作为实现SPD工作流自动化、提升手术准备安全性与一致性、同时缩短SPD处理时间的可扩展性第一步。