通过机器人主动交互感知生物组织状态，提升微创手术自主性。
Object State Estimation Through Robotic Active Interaction for Biological Autonomous Drilling
- 利用接触时的形变反馈估计生物组织状态
- 12次实验中钻孔成功率达91.7%，可分离率75%
- 适合需高精度实时状态感知的微创手术场景
由于显微视觉观测受限，生物样本的状态估计极具挑战。例如，在小鼠颅骨钻孔过程中，由于骨组织半透明且放大倍数高，外观变化极小。为获取物体状态，本文提出一种基于形变反馈的主动交互式状态估计算法，并集成至前期开发的自主钻孔系统中。在12次自主蛋壳钻孔实验中，系统实现91.7%的成功率和75%的可分离率，展现出在更复杂的手术如小鼠颅骨开颅中的应用潜力。该研究为具备主动感知能力的自主机器人系统发展提供了新路径。
原文摘要 · Abstract (English)
Estimating the state of biological specimens is challenging due to limited observation through microscopic vision. For instance, during mouse skull drilling, the appearance alters little when thinning bone tissue because of its semi-transparent property and the high-magnification microscopic vision. To obtain the object's state, we introduce an object state estimation method for biological specimens through active interaction based on the 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.
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