Sensing Model FBG-Based Used for Position and Orientation Detection of Soft Manipulator

To make the end of the soft manipulator reach accurately the designated position, its position and orientation must be measured in real time, which is the basis for motion control and gait planning. In the paper, the sensing network based on the bidirectional helical fiber Bragg grating (FBG) can decouple the coupled strains including tension, bending, and torsion in real time, which removes the restriction of constant axial length in the conventional models. The mapping relationship between the strains and nonlinearity of the soft material determines the deformable parameters. Then, we propose an adaptive following detection (AFD) model to detect the spatial shape and pose by re-coupling the deformable parameters. The model is general enough for any sensor proving the corresponding parameters to sense kinds of soft manipulators (actuated by cable and pneumatic muscle, etc.). We conduct extensive experiments to verify the AFD model. The position and orientation errors of the end are less than 0.23mm and 0.0055rad respectively. The results show that it has the potential to realize the closed-loop control as the feedback signal and provides new ideas for other detection and control models.