Pellet-based fused deposition modeling for the development of soft compliant robotic grippers with integrated sensing elements

Abstract

Abstract Fused deposition modeling (FDM) has some advantages compared to other additive manufacturing techniques, such as the in situ integration of functional components, like sensors, and recyclability of parts. However, conventional filament-based FDM techniques are limited to thermoplastic elastomers with a Shore hardness above 70 A, thus it has marginal compatibility with soft robotic structures. Due to recently emerging pellet-based FDM printer technology, the fabrication of soft grippers with low Shore hardness has become possible. In this study, styrene based thermoplastic elastomers (TPS) were used to print elastic strips and soft gripper structures down to a Shore hardness of 25 A with an integrated strain sensing element (piezoresistive sensor). Printing on a soft rather than rigid substrate affects the integration of the printed thread on the substrate, because of the softness and relaxation, during the printing softness. It was seen that integrating the sensing element on a substrate with higher Shore hardness decreased the elongation at the point of fracture and the sensitivity of the sensing element. A soft compliant gripper structure with an integrated sensing layer was printed with the TPS-based elastomers successfully, and even due to the complex deformation of the compliant gripper structure, several positions could be detected successfully. Opened and closed position of the gripper, as well as, size recognition of spools of different sizes could be monitored by the piezoresistive printed sensor layer. The most sensitive sensing performance was obtained with the TPS of the lower Shore hardness (25 A), as the value of relative change in resistance was 1, followed by the gripper of Shore hardness 65 A and a relative change in resistance of 0.51. With this study, we demonstrated that pellet-based FDM printers can be used, to print potential soft robotic structures with in-situ integrated sensor structures.