We proposed a method for shape sensing using a few multicore fiber Bragg grating (FBG) sensors ina single-port continuum surgical robot (CSR). The traditional method of utilizing a forward kinematic model tocalculate t...We proposed a method for shape sensing using a few multicore fiber Bragg grating (FBG) sensors ina single-port continuum surgical robot (CSR). The traditional method of utilizing a forward kinematic model tocalculate the shape of a single-port CSR is limited by the accuracy of the model. If FBG sensors are used forshape sensing, their accuracy will be affected by their number, especially in long and flexible CSRs. A fusionmethod based on an extended Kalman filter (EKF) was proposed to solve this problem. Shape reconstructionwas performed using the CSR forward kinematic model and FBG sensors, and the two results were fused usingan EKF. The CSR reconstruction method adopted the incremental form of the forward kinematic model, whilethe FBG sensor method adopted the discrete arc-segment assumption method. The fusion method can eliminatethe inaccuracy of the kinematic model and obtain more accurate shape reconstruction results using only a smallnumber of FBG sensors. We validated our algorithm through experiments on multiple bending shapes underdifferent load conditions. The results show that our method significantly outperformed the traditional methodsin terms of robustness and effectiveness.展开更多
基金the National Natural Science Foundation of China(Nos.61873257 and U20A20195)the Project of Natural Science Foundation of Liaoning Province(No.2021-MS-033)the Foundation of Millions of Talents Project of the Department of Human Resources and Social Security of Liaoning Province(No.2021921037)。
文摘We proposed a method for shape sensing using a few multicore fiber Bragg grating (FBG) sensors ina single-port continuum surgical robot (CSR). The traditional method of utilizing a forward kinematic model tocalculate the shape of a single-port CSR is limited by the accuracy of the model. If FBG sensors are used forshape sensing, their accuracy will be affected by their number, especially in long and flexible CSRs. A fusionmethod based on an extended Kalman filter (EKF) was proposed to solve this problem. Shape reconstructionwas performed using the CSR forward kinematic model and FBG sensors, and the two results were fused usingan EKF. The CSR reconstruction method adopted the incremental form of the forward kinematic model, whilethe FBG sensor method adopted the discrete arc-segment assumption method. The fusion method can eliminatethe inaccuracy of the kinematic model and obtain more accurate shape reconstruction results using only a smallnumber of FBG sensors. We validated our algorithm through experiments on multiple bending shapes underdifferent load conditions. The results show that our method significantly outperformed the traditional methodsin terms of robustness and effectiveness.
