Shape Detection Algorithm for Soft Manipulator Based on Fiber Bragg Gratings

• Published in: IEEE/ASME transactions on mechatronics Vol. 21; no. 6; pp. 2977 - 2982
• Main Authors: Hesheng Wang, Runxi Zhang, Weidong Chen, Xinwu Liang, Pfeifer, Rolf
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-12-2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bragg gratings; Curvature; Detection; Fiber Bragg grating (FBG); Fiber gratings; Manipulators; Networks; Robot arms; Robot sensing systems; Shape; shape detection; Shape recognition; soft robot manipulator; Strain
• ISSN: 1083-4435; 1941-014X
• DOI: 10.1109/TMECH.2016.2606491

The shape of soft a manipulator cannot be sensed by the operator directly, when applied to rescue of mine disaster, science exploration, or minimally invasive surgery due to the narrow and closed environment. Shape information is sometimes important for the soft manipulator to be controlled. In order to deal with the problem of shape sensing, a shape sensing algorithm and sensor network based on Fiber Bragg Gratings (FBGs) are introduced in this paper. The shape sensing algorithm is based on piecewise constant curvature and torsion assumption, and can translate the curvature and torsion measured by sensor network into global positions and orientations of nodes. Three-dimensional experiments show that the algorithm introduced in this paper can achieve high accuracy for 3-D shapes.