Shape Sensing for Single-Port Continuum Surgical Robot Using Few Multicore Fiber Bragg Grating Sensors

We proposed a method for shape sensing using a few multicore fiber Bragg grating (FBG) sensors in a single-port continuum surgical robot (CSR). The traditional method of utilizing a forward kinematic model to calculate the shape of a single-port CSR is limited by the accuracy of the model. If FBG sensors are used for shape sensing, their accuracy will be affected by their number, especially in long and flexible CSRs. A fusion method based on an extended Kalman filter (EKF) was proposed to solve this problem. Shape reconstruction was performed using the CSR forward kinematic model and FBG sensors, and the two results were fused using an EKF. The CSR reconstruction method adopted the incremental form of the forward kinematic model, while the FBG sensor method adopted the discrete arc-segment assumption method. The fusion method can eliminate the inaccuracy of the kinematic model and obtain more accurate shape reconstruction results using only a small number of FBG sensors. We validated our algorithm through experiments on multiple bending shapes under different load conditions. The results show that our method significantly outperformed the traditional methods in terms of robustness and effectiveness.