Shape Detection and Reconstruction of Soft Robotic Arm Based on Fiber Bragg Grating Sensor Array

Abstract

For the problem of shape detection and reconstruction of soft robotic arm with extensive degrees of freedom, in this paper, a distributed Fiber Bragg Grating (FBG) sensor array is designed and the shape reconstruction algorithm based on curvature information and the Frenet frame is simplified. The considered soft robotic arm consists of two extension pneumatic muscles (EPMs) in series. Firstly, the distributed FBG sensor array is built. Secondly, the curvature information of each grating point is collected and a continuous curvature curve is obtained by using the interpolation algorithm. Thirdly, the two-dimensional shape curves are reconstructed for the two EPMs according to the simplified shape reconstruction algorithm. Finally, the shape curves of the two EPMs are integrated into the three-dimensional shape curve of the soft robotic arm. Experimental results show that the maximum position error between the end of the reconstructed soft robotic arm and the end of the soft robotic arm is 0.008 $m$, and the percentage error relative to the overall length of the soft robotic arm is 2.58%.