Tactile Perception-Based Depth and Angle Control During Robot-Assisted Bent Bone Grinding

Abstract

During bent bone grinding, the robot often needs to adjust its grinding depth and angle in real time to ensure surgical quality. Optical- or vision-based navigation methods are no longer applicable due to the interference caused by splashing cooling water in the operating field. Inspired by orthopedic surgeons, in this article, we present a tactile perception-based method to solve this problem. The effect of grinding parameters on the cutter's current and vibration is analyzed, and the current and vibration signals are further processed to predict depth and angle. Depth and angle estimation models were calibrated on homogeneous artificial bone. Grinding control experiments were carried out on femur models, and the statistical mean and standard deviation results of the measured depth show that the accuracy of depth control can be further improved by adding angle estimation and proper adjustment when depth is indirectly estimated based on sensing signals. The proposed approach relies solely on the estimation of the relative position and posture between the tool and the bone surface and is expected to improve the safety of automatic grinding with orthopedic robots.