STITCH 2.0: Extending Augmented Suturing with EKF Needle Estimation and Thread Management

Abstract

Suturing is a high-precision task performed at the end of procedures when surgeon fatigue may increase errors, highlighting the need for robot assistance. Previous autonomous suturing works, such as STITCH 1.0 [1], struggle to fully close wounds due to inaccurate needle tracking, thread tangling, and poor insertion placement. To address these challenges, we present STITCH 2.0, an improved augmented dexterity pipeline over STITCH 1.0 using the da Vinci Research Kit (dVRK) [2] with seven improvements including an improved EKF needle pose estimation pipeline, new thread untangling methods, and an automated 3D suture alignment algorithm. Experimental results over 15 trials (maximum 450 individual suture trials) find that STITCH 2.0 achieves 74.4% wound closure with an average of 4.87 sutures per trial, representing 66% more completed sutures in 38% less time compared to STITCH 1.0 [1]. When two human interventions are allowed, STITCH 2.0 averages six sutures with a 100% wound closure rate.