Design and fabrication of a bioinspired synthetic cuticle with embedded sensors for tactile sensing

Tactile sensing is a fundamental aspect of how humans and animals interact with the world. It allows us to manipulate objects, perceive textures, detect slippage, and adjust grip force in real time. However, despite recent advances, most prosthetic and robotic systems still fail to replicate this sense of touch, limiting their overall usability. In this context, insects such as Drosophila melanogaster offer a compelling source of inspiration. Their exoskeleton embeds numerous lightweight and energy-efficient mechanosensors, such as hair bristles and campaniform sensilla, which allow them to quickly and accurately sense forces. This thesis presents the design, fabrication, and testing of a bioinspired, bristle-like tactile sensor. The proposed sensor mimics the geometry and mechanical behaviour of Drosophila hair bristles by using an inclined pillar embedded in a substrate to detect normal forces. A commercial strain gauge is applied at the base of the bristle to transduce deformation into an electrical signal, which is read via a Wheatstone bridge and amplified using an HX711 module interfaced with an Arduino microcontroller. A preliminary finite element analysis was conducted to optimize strain gauge positioning. Bristles were fabricated using a soft silicone mold, and different materials were tested, including polyurethane resin and urethane rubber. To evaluate the sensor’s performance, a simple experimental setup was used to apply repeatable vertical forces to the bristle tip. Preliminary results show the sensor's ability to detect small forces applied at the bristle tip and demonstrate that signal processing algorithms (implemented in MATLAB) can extract event features. The thesis also discusses practical challenges encountered during development, such as air entrapment during casting and mold design limitations. The final part of the work proposes future directions, such as combining multiple sensors working in synergy to better detect and estimate the direction of applied forces. This work contributes to the field of bioinspired tactile sensing by proposing a scalable and customizable sensor architecture tailored for robotic systems engaged in tactile exploration.