Collaborative robots for medical robotics research

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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.