Collaborative robots for medical robotics research

自20世纪80年代以来，机器人已广泛应用于医学研究。机器人可以让医生更精确、更灵活、更可控地完成复杂的手术。我们要求两台Kinova Gen 3轻型协作机器人（cobots）进行医疗机器人研究。这些协作机器人将为机器人辅助程序和机器人和人类远程检查和培训的远程操作的新范例提供前沿研究。这项研究得益于Kinova协作机器人独特的设计和功能，包括模仿人类手部运动的7个自由度（7-DOF），每个关节的力传感，包括深度在内的集成视觉，以及实现快速研究原型的开放式架构。拟议的设备在许多研究任务中取代了非常先进但老化的达芬奇机器人，总结为三个目标。在目标A下，我们将利用Kinova机器人的能力来改变他们的机械阻抗，因为他们的扭矩传感。基于kinova关节力矩传感的7自由度患者侧机械臂（PSM）是探索外科手术中附加、改变和控制手术器械技术的理想基础。同样，基于kinova的外科侧操纵器（MTM）将使力反馈给外科医生，而达芬奇系统则缺乏这种力反馈。我们还将研究虚拟固定装置和综合机构的设计，以指导外科医生的手在手术过程中。在目标B下，我们将制定在医疗程序中提供援助和图像指导的方法。我们将探索在手动、半自动和自主模式下使用超声来指导手术和针头插入，以及在机器人辅助手术期间对内窥镜相机和/或第三只手臂的自主控制。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，还将研究如何使用机器人训练人们执行医疗程序。在目标C下，我们将开发远程操作超声系统，并将探索其性能与人类远程操作相比如何，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社区或资源不足社区的护理成本和质量。该设备将带来医疗机器人技术的重大发现，并将有一条转化之路，以改善偏远社区的护理，并使机器人辅助手术更容易获得，更有效，更便宜。建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10名学生将使用这些设备，进行机器人、视觉、机器学习以及编程和系统集成方面的培训。

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.