血管介入手术机器人系统力反馈的模糊融合

Fuzzy Fusion of Forces Feedback in Vascular Interventional Surgery Robot System

为完善主从式血管介入手术机器人系统,构建了力反馈回路.通过集成两个微型力传感器,实现了对导管前端和侧壁与血管接触力的同时测量.鉴于主从模式与传统手动操作的不同,在进行力觉交互时,为保证医生成熟的手术经验继续发挥作用,采用模糊推理中的双输入–单输出模型完成两路数据的融合.通过标定隶属度函数和制定融合规则表,将积累的手术经验转化为数字化的力反馈策略,不但改善了低采集频率下的力反馈效果,更在准确表征介入状态的同时,针对不同的接触状态实现了不同的反馈分辨率,从而进一步保证了机器人手术系统的适应性、安全性和操作效率.

In order to consummate the master-slave robot system used in vascular interventional procedures,a closed loop of force is rebuilt.Two micro force sensors are integrated with a catheter,which can measure those forces between the tip or side wall of the catheter and vascular walls respectively at the same time.Given that the master-slave mode is different from the traditional hands-on operation and that it is necessary to ensure the sustained effect of the valuable experience from surgeons,a two-input one-output model in fuzzy inference is adopted to accomplish the fusion of the two sensors’ data.By means of calibrating membership functions and establishing a table of fusion rules,experience is converted into numerical strategies about the force feedback,which not only improves the force reflection under low sampling rate,but also characterizes collisions accurately with different resolutions.It ensures the safety,applicability and efficiency of the robot system.