Distributed Curvature Sensing and Shape Reconstruction for Soft Manipulators With Irregular Cross Sections Based on Parallel Dual-FBG Arrays

This article presents a distributed curvature sensing and shape reconstruction method based on parallel dual fiber Bragg grating (FBG) arrays for a type of cable-driven soft manipulator with irregular cross sections. The curvature at each measured point can be detected by the differential response of the relevant dual-FBG sensing unit with less interference from the temperature and axial driven force. The shape of the manipulator can be completely reconstructed by using the integration of the piecewise curvature functions. The measurement principle of curvature and shape reconstruction method have been investigated and derived. Experiments indicate that the constant temperature-induced error for the detected curvature is less than 0.1042 m-1. The error of the detected curvature is small less than -0.0824 m-1within a changing temperature from 30 °C to 50 °C. The shape of the manipulator can be reconstructed with a small error of less than 1 mm under a constant or changing temperature environment. Static and dynamic grasping experiments for the manipulator have been implemented, which indicates a feasible shape tracking with resistance for axial force effect. Such merits further validate the effectiveness of the proposed approach for distributed curvature sensing and shape tracking of the manipulator with irregular cross sections.