STITCH 2.0：通过扩展卡尔曼滤波针位估计与缝线管理增强缝合技术 (STITCH 2.0: Extending Augmented Suturing with EKF Needle Estimation and Thread Management)

Surgical suturing is a high-precision task that impacts patient healing and scarring. Suturing skill varies widely between surgeons, highlighting the need for robot assistance. Previous robot suturing works, such as STITCH 1.0 [1], struggle to fully close wounds due to inaccurate needle tracking and poor thread management. To address these challenges, we present STITCH 2.0, an elevated augmented dexterity pipeline with seven improvements including: improved EKF needle pose estimation, new thread untangling methods, and an automated 3D suture alignment algorithm. Experimental results over 15 trials find that STITCH 2.0 on average achieves 74.4% wound closure with 4.87 sutures per trial, representing 66% more sutures in 38% less time compared to the previous baseline. When two human interventions are allowed, STITCH 2.0 averages six sutures with 100% wound closure rate. Project website: https://stitch-2.github.io/

翻译：外科缝合是一项高精度任务，直接影响患者愈合与疤痕形成。外科医生的缝合技能差异显著，凸显了机器人辅助的必要性。先前的机器人缝合研究（如STITCH 1.0 [1]）因针位跟踪不准确和缝线管理不佳而难以完全闭合伤口。为解决这些挑战，我们提出STITCH 2.0——一个升级的增强灵巧性流程，包含七项改进：改进的扩展卡尔曼滤波针位姿态估计、新型缝线解缠方法以及自动化三维缝合对齐算法。经过15次实验验证，STITCH 2.0平均实现74.4%的伤口闭合率，每次试验完成4.87针缝合，相较于先前基线方法，缝合数量增加66%且耗时减少38%。在允许两次人工干预的情况下，STITCH 2.0平均完成六针缝合，伤口闭合率达100%。项目网站：https://stitch-2.github.io/