In teleoperated robot-assisted surgery, a surgeon operates master manipulators to control the motion of remote robotic manipulators. The manipulators at the remote side enter the patient's body through very small incisions. The patient benefits from the advantages of minimally invasive surgery, while the surgeon's performance is improved by high dexterity and precision inside the patient's body. However, the effectiveness of current clinical systems is limited by the lack of force feedback to the operator. Some surgical procedures, such as exploratory palpation, cannot be performed via MIS. For others, the addition of force information will improve the safety and quality of operation.
Robotic teleoperation systems in critical environments must be stable and transparent. In the classical approaches to analysis and control of teleoperators, there is an inherent trade-off between these two design goals. However, these approaches do not take into account models of the human operator. In previous studies, we explored transparency and the human operator. Here, we intend to explore the human operator influence on stability, and develop new control methods for teleoperated surgery that consider biomechanical and neurological models of the operator.
In particular, we will push the boundary of the stability-transparency tradeoff, and maintain stable system performance with useful force feedback. To achieve this, we will collaborate with surgeons to identify performance measures and perception goals. We will develop human-in-the-loop stability analysis and use recent results in human motor control to develop the control methods. These will be applied on a custom research version of a clinical robotic surgery system in realistic surgical tasks.
This study is expected to enable effective and practical force feedback for teleoperated robotic surgery, and open new capabilities for surgery and other telerobotic applications.
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