J Shanghai Jiaotong Univ Sci

J Shanghai Jiaotong Univ Sci ›› 2023, Vol. 28 ›› Issue (3): 312-322.doi: 10.1007/s12204-023-2579-x

Special Issue: 智能机器人

• Special Issue on Advanced Technologies for Medical Robotics • Previous Articles     Next Articles

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

基于少量多核光纤光栅传感器的单孔连续体手术机器人形状感知

LI Dingjia1,2,3,4(黎定佳)，WANG Chongang1,2,3(王重阳)，GUO Wei5(郭伟)，WANG Zhidong6(王志东)，ZHANG Zhongtao5(张忠涛)，LIU Hao1,2,3*(刘浩)   

  1. (1. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; 2. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China; 3. Liaoning Province Key Laboratory of Minimally Invasive Surgical Robot, Shenyang 110016, China; 4. University of Chinese Academy of Sciences, Beijing 100049, China; 5. Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China; 6. Chiba Institute of Technology, Narashino 275-0016, Chiba, Japan)
  2. （1. 中国科学院 沈阳自动化研究所机器人学国家重点实验室，沈阳110016; 2. 中国科学院 机器人与智能制造创新研究院，沈阳110169; 3. 辽宁省微创手术机器人重点实验室，辽宁 沈阳110016; 4. 中国科学院大学，北京100049; 5. 首都医科大学附属北京友谊医院，北京100050; 6. 千叶工业大学，日本千叶县 习志野275-0016)
  • Received:2022-06-30 Revised:2022-08-25 Accepted:2023-05-28 Online:2023-05-28 Published:2023-05-22

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Abstract: 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.

Key words: single-port continuum surgical robot, multicore fiber Bragg grating (FBG), forward kinematic model, extended Kalman filter (EKF), shape reconstruction

摘要： 本文提出了一种在单孔连续体手术机器人（CSR）中使用少量多核光纤光栅（FBG）传感器进行形状感知的方法。传统的方法利用正运动学模型计算单孔CSR的形状，其受到模型精度的限制。如果将FBG传感器用于形状传感，其精度将受到传感器数量的影响，特别是在长而灵活的CSR中。为了解决这一问题，提出了一种基于扩展卡尔曼滤波（EKF）的融合方法。分别使用CSR正运动学模型和FBG传感器进行形状重建，并用EKF将两个结果融合。CSR运动模型的方法采用了正运动学模型的增量形式进行形状重建，FBG传感器的方法则采用了离散弧段假设进行形状重建。融合方法可以消除运动学模型的不准确性，仅使用少量FBG传感器即可获得更精确的形状重建结果。通过不同载荷条件下多种弯曲形状的实验验证了该算法的有效性。结果表明，该方法在鲁棒性和有效性方面明显优于传统方法。

关键词: 单孔连续体手术机器人，多芯光纤光栅，正运动学模型，扩展卡尔曼滤波，形状重建

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