Soft robotics presents several advantages in the field of minimally invasive surgery. However, existing methods have not fully addressed problems related to soft robot shape sensing due to the complex motion of soft robots and the stretchable nature of the soft materials employed. This study demonstrates the shape sensing of a soft robot with a helically embedded stretchable fibre Bragg grating (FBG)-based optical fibre sensor. Unlike straight FBG embedding configurations, this unique helical configuration prevents sensor dislocation, supports material stretchability, and facilitates shape detection for various soft-robot movements. The proposed soft-robot design principle and FBG sensor are analysed and their fabrication process, which includes an FBG-written optical fibre sensor, is described. Bending experiments are conducted with the soft robot, the wavelengths of FBG sensors at different bending and telescopic movement states are obtained, and the soft-robot shape is reconstructed. Experimental results demonstrate that the maximum error between FBG sensing and the actual bending state is less than 2.5%, validating the feasibility and effectiveness of the proposed helical stretchable FBG sensing method for the shape measurement of soft robots. These results indicate the potential and applicability of this shape-sensing approach in biomedical research.
To meet the practical application requirements of cardiac fixation during off-pump coronary artery bypass surgery, a soft cardiac fixator with a flexible arm was previously designed. To enable the soft cardiac fixator to adapt to uncertain external forces, this study evaluates the variable-stiffness performance of the flexible arm. First, the flexible arm was simplified as a soft silicone manipulator measuring 60 mm × 90 mm × 120 mm, which can actuate, soften, or stiffen independently along the length of the arm by combining granular jamming with input pressure. Then, the soft manipulator was modelled as a cantilever beam to analyse its variable-stiffness performance with granular jamming. Next, based on theoretical analysis and calculations, many experiments were conducted to evaluate the variable-stiffness performance of the soft manipulator. The experimental results demonstrated that the variable-stiffness performance is influenced by the flexible arm length, the size of the granules, and the input pressure.
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