Dynamic Active Constraints for Surgical Robots Using Vector-Field Inequalities
Dynamic Active Constraints for Surgical Robots Using Vector-Field Inequalities
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DOI：
10.1109/tro.2019.2920078
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发表时间：
2018-04
影响因子：
7.8
通讯作者：
M. M. Marinho-M.;Bruno Vilhena Adorno;K. Harada;M. Mitsuishi
中科院分区：
文献类型：
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作者：
M. M. Marinho-M.;Bruno Vilhena Adorno;K. Harada;M. Mitsuishi
机器人辅助使外科医生能够进行灵巧和无震颤的手术，但机器人辅助在限制性手术中的代表性仍然不足，例如深部脑神经外科手术和鼻内手术。在这些手术中，外科医生将视野限制在手术工具提示附近的区域，这增加了器械轴与其周围环境之间意外碰撞的风险。在本文中，我们的矢量场不等式方法扩展到提供动态主动约束的任何数量的机器人和移动物体共享同一工作空间。该方法进行了评估与实验和模拟中，机器人工具，以避免碰撞自主和实时，在一个受约束的鼻内手术环境。仿真结果表明，该方法使两个机器人系统的综合轨迹误差最优。使用真实的机器人系统的实验表明，该方法可以自主地防止机器人之间的碰撞和机器人与环境之间的运动。此外，该框架也成功地验证下的工具与组织的相互作用的遥操作。
Robotic assistance allows surgeons to perform dexterous and tremor-free procedures, but robotic aid is still underrepresented in procedures with constrained workspaces, such as deep brain neurosurgery and endonasal surgery. In these procedures, surgeons have restricted vision to areas near the surgical tooltips, which increases the risk of unexpected collisions between the shafts of the instruments and their surroundings. In this paper, our vector-field-inequalities method is extended to provide dynamic active-constraints to any number of robots and moving objects sharing the same workspace. The method is evaluated with experiments and simulations in which robot tools have to avoid collisions autonomously and in real-time, in a constrained endonasal surgical environment. Simulations show that with our method the combined trajectory error of two robotic systems is optimal. Experiments using a real robotic system show that the method can autonomously prevent collisions between the moving robots themselves and between the robots and the environment. Moreover, the framework is also successfully verified under teleoperation with tool–tissue interactions.