Omnidirectionally Strain-Unperturbed Tactile Array from Modulus Regulation in Quasi-Homogeneous Elastomer Meshes

Skin-like stretchable tactile arrays are of paramount significance for perceiving physical interactions in dynamic biological tissues, prosthetic limbs, and robots. However, mechanical strain-induced interference invariably degrades the pressure-sensing accuracy of tactile arrays. In this work, an omnidirectionally strain-unperturbed tactile array is prepared through modulus regulation in quasi-homogeneous elastomer meshes. By varying fiber orientations, the proportion of intrinsic elastic and structural deformations in quasi-homogeneous elastomer meshes can be adjusted, and the modulus can be regulated from 0.23 to 8.23 MPa. The tactile array combined with low- and high-modulus elastomer meshes enables strain-unperturbed pressure sensing through local stiffening and controllable deformation. Remarkably, the tactile array exhibits 97% strain insensitivity when stretched 100% along the omniplane directions. Moreover, the quasi-homogeneous structure endows the tactile array with high robustness, even after 5000 cycles of severe stretching or pressing. By integrating the tactile array with a microcontroller, a tactile visualization system is built to achieve accurate tactile interaction even under multiaxial tensile strain. This work provides an alternative insight into the design of omnidirectionally strain-unperturbed electronic devices for wide applications on dynamic surfaces. Elastomer meshes with designable modulus are prepared by regulating the orientations of fibers. Quasi-homogenous elastomer mesh combined with low-modulus polyurethane fibers and high-modulus polyurethane fibers with carbon nanotubes is further obtained, which enables tactile array to achieve omnidirectionally strain-unperturbed pressure sensing through local stiffening and controllable deformation. The quasi-homogeneous structure endows tactile array with high robustness even after undergoing long-term severe mechanical deformation.image