Towards collaborative and autonomous robotic minimally invasive surgery

该研究项目的目标是开发用于协作和自主机器人手术的人机界面和方法。自从机器人进入手术室以来，外科手术经历了医学史上最大的变化之一。在远程手术中，针头和导管等医疗工具由外科医生使用机械臂进行远程操作。最近的进展引发了外科机器人的新趋势，从手术中工具的导航到自主和半自主干预的发展，导致了几个开放式的研究挑战。我建议开发协作和完全自主的机器人干预方法，将两个互补的研究领域结合在一起，即手术工具的基于超声波的图像引导和手术任务的人机协同遥操作。*基于谐波超声成像，该研究计划将开发使用非线性超声的方法，以自动和稳健地跟踪插入人体组织的手术工具。根据组织对给定位置处的超声信号的反应，可以估计组织的机械性能。然后，直接触摸和触碰组织的感觉可以使用触觉反馈远程传达给外科医生。这也将为外科医生提供安全屏障和指导，以增加对正在执行的任务的认知感知。我建议将轨迹规划和学习算法结合起来，在向机器人传授所需动作的同时，补偿其环境的动态变化。潜在的应用包括治疗肝癌、前列腺癌、肾癌、胰腺癌、脑癌和膀胱癌，以及白内障手术，以及局部药物和植入物输送。*拟议的研究将使研究生和本科生能够在与机器人手术创新最先进技术的发展相关的关键领域进行培训，这对加拿大来说前景广阔。

The objective of this research program is to develop human-machine interfaces and methods for collaborative and autonomous robotic surgery. Ever since robots have entered the operating room, surgery has gone through one of the greatest changes in the history of medicine. In teleoperated surgery, medical tools such as needles and catheters are operated remotely by a surgeon using a robotic arm. Recent advances gave rise to new trends in surgical robots spanning from intra-operative navigation of tools to the development of autonomous and semi-autonomous interventions, resulting in several open-ended research challenges. I propose to develop methods that allow for collaborative and fully autonomous robotic interventions that will combine two complementary research areas, namely ultrasound-based image guidance of surgical tools and human/machine cooperative teleoperation of surgical tasks.******Based on harmonic ultrasonic imaging, this research program will develop methods using nonlinear ultrasound to automatically and robustly track surgical tools inserted into human tissue. From the reaction of the tissue to the ultrasound signals at a given location, the mechanical properties of the tissue can be estimated. The sensation of directly touching and palpating the tissue can then be conveyed to the surgeon remotely using haptic feedback. This will also provide surgeons with safety barriers and guidance to increase the cognitive perception of the task being performed. I propose to combine trajectory planning and learning algorithms to teach a required action to the robot while compensating for dynamic changes in its environment. Potential applications include treatments for liver, prostate, kidney, pancreatic, brain, and bladder cancers, as well as cataracts surgery, and localized drug and implant delivery.******The proposed research will enable training of graduate and undergraduate students in key areas pertaining to the development of innovative state-of-the-art technologies for robotic surgery, which hold great promise for Canada.