TY - JOUR
T1 - Modular and Fault-Tolerant Three-Axial FBG-Based Force Sensing for Transoral Surgical Robots
AU - Li, Tianliang
AU - Huang, Ping'An
AU - Wang, Shasha
AU - Qiu, Liang
AU - Li, Changsheng
AU - Ren, Hongliang
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2024
Y1 - 2024
N2 - Transoral robotic surgery (TROS) has met a significant challenge to precise control of surgical instruments and depress the injury risks without force feedback. Therefore, we develop a modular high-precision three-axial fiber Bragg grating (FBG) force sensor with nonlinear decoupling, fault tolerance, and temperature compensation (TC) for seamless integration into transoral robots. The sensor comprises a one-body elastomer housing four optical fibers engraved with FBG each, arranged at a constant interval of 90° along the circumference to enhance three-axial force perception through redundancy. A novel dung Beetle optimization extreme learning machine (DBO-ELM) algorithm is proposed to tackle nonlinear coupling, FBG fracture, and temperature interference challenges leading to excellent performances of accurate and reliable measurement. The maximum full-scale error is less than 4% in each dimension, and the maximum MSE is only 1.8 mN at various spatial angles. The combination of four redundant FBGs and the DBO-ELM fault-tolerant model enables high-precision fault tolerance with maximum full-scale relative errors below 6% in case of one FBG damage. After TC, the maximum force measurement error is within 4% of the range. These merits confirm the effectiveness and dependability of the proposed sensor and algorithms in TROS applications.
AB - Transoral robotic surgery (TROS) has met a significant challenge to precise control of surgical instruments and depress the injury risks without force feedback. Therefore, we develop a modular high-precision three-axial fiber Bragg grating (FBG) force sensor with nonlinear decoupling, fault tolerance, and temperature compensation (TC) for seamless integration into transoral robots. The sensor comprises a one-body elastomer housing four optical fibers engraved with FBG each, arranged at a constant interval of 90° along the circumference to enhance three-axial force perception through redundancy. A novel dung Beetle optimization extreme learning machine (DBO-ELM) algorithm is proposed to tackle nonlinear coupling, FBG fracture, and temperature interference challenges leading to excellent performances of accurate and reliable measurement. The maximum full-scale error is less than 4% in each dimension, and the maximum MSE is only 1.8 mN at various spatial angles. The combination of four redundant FBGs and the DBO-ELM fault-tolerant model enables high-precision fault tolerance with maximum full-scale relative errors below 6% in case of one FBG damage. After TC, the maximum force measurement error is within 4% of the range. These merits confirm the effectiveness and dependability of the proposed sensor and algorithms in TROS applications.
KW - Fault-tolerant
KW - fiber Bragg grating (FBG) based three-axial force sensor
KW - nonlinear decoupling
KW - redundant effect
KW - transoral robotic surgery (TROS)
UR - http://www.scopus.com/inward/record.url?scp=85191733255&partnerID=8YFLogxK
U2 - 10.1109/TIE.2024.3376814
DO - 10.1109/TIE.2024.3376814
M3 - Article
AN - SCOPUS:85191733255
SN - 0278-0046
VL - 71
SP - 16739
EP - 16750
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 12
ER -