Virtual prototyping of vision-based tactile sensors design for robotic-assisted precision machining

Abstract

Vision-Based Tactile Sensors (VBTS) play a key role in enhancing the accuracy and efficiency of machining operations in robotic-assisted precision machining systems. Equipped with VBTS, these systems offer contact-based measurements, which are essential in machining accurate components for industries such as aerospace, automotive, medical devices, and electronics. This paper presents a novel approach to virtual prototyping of VBTS, specifically in perpendicularity measurements using Computer-Aided Design (CAD) generation of VBTS designs, Finite Element Analysis (FEA) simulations, and Sim2Real deep learning to achieve VBTS with high precision measurements. The virtual prototyping approach enables an understanding of the contact between VBTS with different designs and machined surfaces in terms of contact module shape, thickness, markers’ density. Additive manufacturing was employed to fabricate the molds of VBTS contact module, followed by experimental validation of the robotic arm to confirm the effectiveness of the optimized VBTS design. The results show that deviation from the hemispherical shape reduces the data quality captured by the camera, hence increasing the prediction errors. Additionally, reducing the thickness of the contact module enhances the precision of perpendicularity measurements. Importantly increasing markers’ distribution density significantly enhances the accuracy of up to 92 markers at which above it the rate of improvement becomes less pronounced. An VBTS with height of 20mm, thickness of 2mm, and 169 markers was found to be within the stringent perpendicularity standards of the aerospace manufacturing industry of 0.58∘ as a root mean square error, and 1.64° as a max absolute error around the roll and pitch axis of rotation. The established virtual prototyping methodology can be transferred to a wide variety of elastomer-based sensors.