Object State Estimation Through Robotic Active Interaction for Biological Autonomous Drilling

Estimating the state of biological specimens is challenging due to limited observation through microscopic vision. For instance, during mouse skull drilling under high-magnification microscopic vision, the appearance alters little when thinning bone tissue because of its semi-transparent visual properties. To obtain the object's state, we introduce an object state estimation method for biological specimens through active interaction based on deflection. The method is integrated to enhance the autonomous drilling system developed in our previous work. The method and integrated system were evaluated through 12 autonomous eggshell drilling experiment trials. The results show that the system achieved a 91.7% successful ratio and 75% detachable ratio, showcasing its potential applicability in more complex surgical procedures such as mouse skull craniotomy. This research paves the way for further development of autonomous robotic systems capable of estimating the object's state through active interaction.