Hybrid Data-Driven Optimization Design of a Layered Six-Dimensional FBG Force/Moment Sensor with Gravity Self-compensation for Orthopedic Surgery Robot

In this article, we develop a layered six-dimensional (6-D) FBG force sensor to detect the interaction force between drill and tissue in robot-assisted bone drilling. Eight unique C-shaped beams are arranged in layers within the structure to constitute a force-sensitive 3-D-printed flexure body and eight FBGs have been tensely suspended on the concave side of beams, leading to low chirping risk and low cost of the designed sensor. A mathematical sensing model of the designed sensor has been derived by response surface methodology with the hybrid data obtained from experiments and the finite-element method. Multiobjective optimization model of the sensor with consideration of machining deviation has been built, and its measurement isotropy for force and moment has increased by 31.4% and 30.7%, respectively, as well as the enhancement of the capabilities of the interdimensional decoupling and toleration for machining deviation. The experimental results demonstrate a low coupling error and a high resonant frequency of more than 232 Hz. The relative error of the sensor is less than 8.27%. A robot-assisted bone drilling experiment has been implemented to further confirm the feasibility and reliability of the sensor. By innovatively integrating a gravity self-compensation method, the sensor's detected force agrees with the reference result with a less error of 7.4%.