Robust Three-Dimensional Shape Sensing for Flexible Endoscopic Surgery Using Multi-Core FBG Sensors

In this letter, we propose a novel 3D shape sensing algorithm for flexible endoscopic surgery using multi-core fiber Bragg grating (FBG) sensors. Considering the signal noises and environmental perturbations, the direct use of FBG measurements for shape sensing and position estimation is regarded as far from accurate and stable, especially when utilized in the sensing of long and flexible surgical instruments. To solve this problem, a novel and generic model-based filtering technique for the iterative curvature/twist estimation by taking advantage of the configurations of the multi-core FBGs in the optical fiber is introduced to remedy the sensory noises. Besides, we introduce an enhanced moving average approach to smooth the estimated curvatures and twists spatially on the fiber. We extensively validate our algorithm by conducting shape sensing tasks in simulations under varying conditions, and in experiments using a robotic-assisted colonoscope system integrated with a multi-core FBG fiber. The results prove our method substantially outperforms the conventional approach in the aspect of estimation accuracy and robustness, showing the superiority and application feasibility.

Automated summary

This study presents a novel 3D shape sensing algorithm for flexible endoscopic surgery using multi-core fiber Bragg grating sensors, with a model-based filtering technique and enhanced moving average approach to address signal noises and enhance estimation accuracy.