Depth-estimation of stiffness singularity in an elastic object via directional touch sensing using microfinger with tactile sensor

Understanding object information during robotic hand grasping is a key goal in robotics. Researchers have integrated tactile sensors to replicate artificial haptics on humanoid robot fingertips, but robotic grasping has yet to be fully applied in palpation-based medical diagnosis. Current techniques, such as vibration-based ultrasound-assisted surgeries, face limitations in diagnosis due to anatomical constraints or surgical access issues. To address this, we explored palpation-assisted surgeries using a microfinger, a miniaturized version of a human finger. We developed micromachine-based palpation techniques for advanced minimally invasive diagnosis using endoscopes. Specifically, we developed a microfinger with artificial muscle and tactile sensors, designed to detect stiffness singularities in pseudo-biological tissues. Our microfinger, thin and small, exerted a pushing force greater than 1 N and performed directional palpation. Next, we proposed an algorithm for estimating three-dimensional coordinates, thus transcending the existing two-dimensional singularity-estimation method. Consequently, we achieved touch sensing on silicone gel blocks using a small rigid ball, with depth-estimation of approximately ± 1.3 mm at a depth of 15 mm. The directivity of the microfinger enabled three-dimensional positional estimation of the singular point. We present a breakthrough for microfinger-based palpation technology for medical diagnosis, accelerating the advancement of robotics-based palpation-driven minimally invasive techniques.