Research On The FBG-based Force And Shape Sensing System For Minimally Invasive Surgical Robot

Recently,the integration of force and shape sensing system on different robot has become one of the worldwide research hotspots in field of robotics.At the same time,the sensing functions appear to be more and more important for minimally invasive surgical robots with specific structures,application background and operation environment.Considering this and with the support of the State Key Laboratory of Robotics and Systems,we designed a force and shape sensing system based on the fiber Bragg grating(FBG)sensor for a specific laparoscopic single-site surgical robot,aiming to provide more R&D ideas,research experience and feasible methods for related scientific studies as well as medical industry.In order to gain a clearer picture of the status quo,we first focused on the previous studies related to FBG-based forces and shape sensing system that design for various surgical robots at home and abroad.Related work had been detailed investigated.Design standards in the mainstream application background were drawn.Design scheme,design principles and design methods of the FBG-based force and shape sensing system were also given,along with the existing difficulties and future trends of this direction.For the sensing system design,standard laparoscopic surgical robot(LSR)and laparoscopic single-site surgical robot(LSSR)were considered as the subject,based on which we designed the corresponding FBG-based force and shape sensing system according to specific mechanical structure,actuation method and working environment.Research of the force sensing system design included mechanical design of the FBGbased force sensing system,establishment of the corresponding mechanical model,and development of the triaxial force and temperature decoupling mechanism;while research of the shape sensing system design included the design of FBG-based shape sensing system for LSSR and the development of the 3D skeleton reconstruction algorithm based on Frenet-Serret formula.As force and shape sensing mechanical design accomplished,we both employed the finite element method(FEM)analysis to demonstrate the strain concentration of the designed structure.For the force sensing part,to improve the sensing performance of the elastic joints,several sensitivity indexes were derived(as the optimization targets)by developing the mechanical model of the joint,after which a modified particle swarm optimization method was applied to optimize its key mechanical parameters.For the shape sensing part,in order to reduce the risk that the fiber could break under hard bending,we specially designed a novel flexible robot arm carrying the FBG sensing system with a sub-flexible-flexible joint staggered arrangement.The BP neural network was employed to calibrate the curvature correlation between the joints for improving the shape reconstruction accuracy as well as the system complexity.To also enhance the practicability of the developed reconstruction algorithm,a graphical user interface(GUI)was developed within the Matlab App Designer environment.For the force sensing experimental,a 4 degree-of-freedom platform with a remote center of motion(RCM)mechanism able to realize different spatial configurations was built,along with a special devised platform to facilitate the manual integration process of the FBG-based force sensing system.Both the Least square method and BP neural network were employed to calibrate the FBG-based force sensing system while the performances were all compared and evaluated concerning the design criteria.For the shape sensing part,a 2-DOFs LEER arm was developed by following the sub-flexible-flexible joint staggered arrangement design.Integration of the designed FBG-based shape sensing system was preliminary completed.Unfortunately,due to the inconvenience introduced by COVID-19,subsequent experiment was failed to finish.