Collaborative robots for medical robotics research

自20世纪80年代以来，机器人已被广泛用于医学研究。机器人使医生能够以更高的精度、灵活性和控制力执行复杂的手术。我们要求两个Kinova Gen 3轻型协作机器人（cobots）进行医疗机器人研究。这些协作机器人将使机器人辅助程序的新范式的尖端研究以及机器人和人类的远程操作能够进行远程检查和培训。Kinova协作机器人独特的设计和功能使这项研究得以实现，包括模仿人手运动的七个自由度（7-DOF）、每个关节的力感、包括深度在内的集成视觉以及能够实现快速研究原型的开放式架构。拟议的设备取代非常先进，但老化的达芬奇机器人在一些研究任务，总结在三个目标。 在目标A下，我们将利用Kinova机器人的能力来改变它们的机械阻抗，因为它们的扭矩传感。一个7自由度Kinova为基础的病人侧机械手（PSM）与关节扭矩传感是一个理想的基础，我们探索附加的技术，改变和控制手术器械在外科手术远程操作。类似地，基于Kinova的外科医生侧操纵器（MTM）将使得能够向外科医生提供力反馈，其中da芬奇系统遭受缺乏这种力反馈的问题。我们还将研究虚拟夹具和合成机制的设计，以在手术过程中指导外科医生的手。 根据目标B，我们将开发在医疗程序中提供帮助和图像引导的方法。我们将探索使用超声引导手术和针插入，在手动，半自动和自主模式，以及自主控制的内窥镜摄像机和/或第三臂在机器人辅助手术。此外，我们不仅将研究如何训练机器人自主执行医疗程序，如超声波，而且还将研究如何使用机器人来训练人们执行医疗程序。 在目标C下，我们将开发远程操作的超声系统，并将探索它们的性能与人类远程操作的比较，其中由专家控制的远程机器人被具有增强现实界面的人类新手所取代。这项研究有可能大大提高小型或资源不足社区的护理成本和质量。拟议的设备将导致医疗机器人技术的重要发现，并将有一个翻译路径，以改善对偏远社区的护理，并使机器人辅助手术更容易获得，更有效，更便宜。 拟议的设备将由至少七名研究人员使用，包括三名共同申请人;每年至少有十名学生将使用这些设备，从而能够进行机器人技术，视觉，机器学习以及编程和系统集成技能的培训。

Robots have been widely used in medical research since the 1980s. Robots allow doctors to perform complex procedures with more precision, flexibility and control. We request two Kinova Gen 3 lightweight collaborative robots (cobots) to carry out medical robotics research. These cobots will enable cutting-edge research in new paradigms for robot-assisted procedures and teleoperation of both robots and humans for remote examination and training. The research is enabled by the Kinova cobots' unique design and capabilities, including seven degrees of freedom (7-DOF) mimicking human hand motion, force sensing at every joint, integrated vision, including depth, and an open architecture that enables rapid research prototyping. The proposed equipment replaces very advanced but aging da Vinci robots in a number of research tasks, summarized in three objectives. Under Objective A, we will exploit the ability of the Kinova robots to change their mechanical impedance because of their torque sensing. A 7-DOF Kinova-based patient-side manipulator (PSM) with joint torque sensing is an ideal base for us to explore additional techniques of attaching, changing, and controlling the surgical instruments during surgical teleoperation. Similarly, a Kinova-based surgeon-side manipulator (MTM) will enable force feedback to the surgeon where the da Vinci system suffers from lack of this force feedback. We will also research the design of virtual fixtures and synthetic mechanisms to guide the hands of the surgeon during a procedure. Under Objective B, we will develop methodologies to provide assistance and image guidance during medical procedures. We will explore the use of ultrasound to guide surgery and needle insertion, in manual, semi-automatic and autonomous modes, as well as autonomous control of the endoscopic camera and/or a third arm during robot-assisted surgery. Additionally, we will research not only how to train robots to perform medical procedures such as ultrasound autonomously, but also how to use the robots to train people to perform the medical procedures. Under Objective C, we will develop teleoperated ultrasound systems and will explore how their performance compares with human teleoperation, where the remote robot that is controlled by the expert is replaced by a human novice with an augmented reality interface. This research has the potential to greatly improve the cost and quality of care for small or under-resourced communities. The proposed equipment will lead to important discoveries in medical robotics and will have a translation path to improve care for remote communities and to make robot-assisted surgery more accessible, more effective, and less expensive. The proposed equipment will be used by at least seven investigators, including the three co-applicants; at least ten students will be using the equipment every year, enabling training in robotics, vision, machine learning and developing skills in programming and system integration.