Towards Autonomous Instrument Tray Assembly for Sterile Processing Applications

2026-02-02

AI Summary

This study addresses the inefficiencies, contamination risks, and instrument damage associated with manual assembly of surgical instrument trays. To overcome these challenges, the authors propose the first robotic system capable of fully automating tray assembly within the Sterile Processing Department (SPD) workflow. The system integrates YOLOv12 for object detection, a cascaded ResNet architecture for fine-grained classification, a calibrated vision module, and a Stäubli TX2-60L six-axis robotic arm equipped with a custom dual electromagnetic gripper. Innovatively, 3D-printed spacers and a rule-based tray-packing algorithm are introduced to prevent instrument collisions during loading. Evaluated on a self-constructed dataset comprising 31 instrument categories, the system demonstrates high-precision perception, significantly improving packing consistency, sterile processing efficiency, and reducing the risk of instrument damage.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Federated Web and WoT systems, including distributed, federated and edge-based data processing
• Security and Privacy: Tracking, profiling, and countermeasures against them

Abstract

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.

Problem

• Sterile Processing
• Instrument Tray Assembly
• Surgical Instrument Handling
• Automation in Healthcare
• SPD Workflow

Innovation

• robotic automation
• surgical instrument assembly
• hybrid perception pipeline
• collision-aware packing
• sterile processing