Hybrid Motion Control of a Fiber-based Soft Robotic Instrument for Minimally Invasive Surgery

Abstract

Minimally Invasive Surgery (MIS) reduces surgical risks and recovery times by enabling precise interventions around lesion sites. However, accessing these sites requires flexible instruments, which often compromise the precision afforded by rigid devices. This study proposes a thermally drawn fiber-based, tendon-driven soft robotic instrument with a two-stage hybrid motion control framework to enhance accuracy. Several learning-based inverse kinematic (IK) models were developed, with the LSTM-based model showing the best performance and used to guide open-loop large-scale motion, while a closed-loop controller refines accuracy via real-time feedback. The system is validated by path-following tasks and a simulated endometrial ablation in a vaginal phantom. Results show that the IK model realizes stable open-loop control with Euclidean error below 2 mm, while hybrid control further reduces errors to below 1 mm. This combination offers a promising MIS solution with high precision in difficult-to-reach surgical sites.