Towards collaborative and autonomous robotic minimally invasive surgery

该研究计划的目标是开发人机界面和协作和自主机器人手术的方法。自从机器人进入手术室以来，外科手术经历了医学史上最伟大的变革之一。在远程手术中，外科医生使用机器人手臂远程操作针头和导管等医疗工具。最近的进展引发了手术机器人的新趋势，从手术工具的术中导航到自主和半自主干预的发展，导致了一些开放式的研究挑战。我建议开发的方法，允许协作和完全自主的机器人干预，将联合收割机两个互补的研究领域，即基于超声的图像引导的手术工具和人/机合作的手术任务的远程操作。 基于谐波超声成像，该研究计划将开发使用非线性超声自动和鲁棒地跟踪插入人体组织的手术工具的方法。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特性。然后，可以使用触觉反馈将直接触摸和触诊组织的感觉远程地传达给外科医生。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。我建议结合联合收割机的轨迹规划和学习算法，教机器人所需的动作，同时补偿其环境中的动态变化。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，以及白内障手术和局部药物和植入物递送。 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技术的发展有关的关键领域进行培训，这对加拿大来说是一个巨大的希望。

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.