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arXiv · 2608.14772

MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery

Robin Koch·Annabella Mascot·Rayan Younis·Martin Wagner·Stefanie Speidel·Mark Cutkosky·Ingo Sieber·Roberto Calandra
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Abstract

Minimally invasive and robot-assisted surgery offer many advantages over traditional open surgery, but deprive surgeons of tactile feedback and the ability to palpate tissue with their fingers. To address this lack of tactile feedback, we introduce the MISTac, a high resolution vision-based tactile sensor specifically designed for palpation in MIS. The sensor has a replaceable sensor tip with a diameter of 8 mm which allows it to fit through the trocars used in minimally invasive surgery. Its modular 3D-printed case design allows the use of bulky off-the-shelf illumination and imaging hardware that can easily be exchanged and upgraded. The sensor has an optical resolution of 176.68 $\mu m$, a tactile resolution of 250 $\mu m$, and can resolve forces as little as 24.3 mN. An in vivo study with the sensor shows its usability in minimally invasive surgery. We trained a machine learning model with the tactile data collected in the trial on a tissue classification task achieving an aggregate accuracy of ~84% in a leave-one-out cross validation. Tactile sensors have the potential to one day aid surgeons during minimally invasive surgery with tasks such as tissue classification or intra-operative tumor localization; MISTac is a small step towards this vision. We open-source MISTac at https://github.com/lasr-lab/mistac

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Robin Koch, Annabella Mascot, Rayan Younis, Martin Wagner, Stefanie Speidel, Mark Cutkosky, Ingo Sieber, Roberto Calandra. 2026-08-14. MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery. https://arxiv.org/abs/2608.14772

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