Abstract-Robotic surgery is transforming the current surgical practice, not only by improving the conventional surgical methods but also by introducing innovative robot-enhanced approaches that broaden the capabilities of clinicians. Being mainly of manmachine collaborative type, surgical robots are seen as media that transfer pre-and intra-operative information to the operator and reproduce his/her motion, with appropriate filtering, scaling, or limitation, to physically interact with the patient. The field, however, is far from maturity and, more critically, is still a subject of controversy in medical communities. Limited or absent haptic feedback is reputed to be among reasons that impede further spread of surgical robots. In this paper objectives and challenges of deploying haptic technologies in surgical robotics is discussed and a systematic review is performed on works that have studied the effects of providing haptic information to the users in major branches of robotic surgery. It has been tried to encompass both classical works and the state of the art approaches, aiming at delivering a comprehensive and balanced survey both for researchers starting their work in this field and for the experts.
Robot human-like behavior can enhance the performance of human-robot cooperation with prominently improved natural interaction. This also holds for redundant robots with an anthropomorphic kinematics. In this article, we translated human ability of managing redundancy to control a seven degrees of freedom anthropomorphic robot arm (LWR4þ, KUKA, Germany) during tele-operated tasks. We implemented a nonlinear regression method-based on neural networks-between the human arm elbow swivel angle and the hand target pose to achieve an anthropomorphic arm posture during tele-operation tasks. The method was assessed in simulation and experiments were performed with virtual reality tracking tasks in a lab environment. The results showed that the robot achieves a human-like arm posture during tele-operation, and the subjects prefer to work with the biologically inspired robot. The proposed method can be applied in control of anthropomorphic robot manipulators for tele-operated collaborative tasks, such as in factories or in operating rooms.
Service robots and even industrial robots recently started sharing human workspace for creating new working settings where humans and robots work even hand by hand. On the one hand, this new scenario raises problems of safety, which are being solved by adding suitable sensor batteries to robot control systems, and on the other hand, it entails dealing with psychophysical aspects as well. Motion intention understanding and prediction comes more natural and effective if the controlled movement is biologically inspired. In order to generate biologically inspired movements in a robotic-assisted surgery scenario, where a robotic assistant shares the execution of tasks with, or hands over tools to a surgeon, we designed a trajectory planning system based on an artificial neural network architecture trained on human actions. After the design and training of the neural controller for motion planning, we checked the objective characteristics of the achieved biologically inspired motion as functional minimization (minimum jerk), two-third power law and bell-shaped velocity. The controller was also experimentally implemented by using a redundant serial robotic arm (LWR4+, Kuka, Germany), and it was actually perceived as "human-like" in the majority of cases by naive subjects. The implemented neural-based control strategy provided to be an effective scheme for human-robot interaction control, also by qualitative assessment.
In abdominal surgery, intraoperative bleeding is one of the major complications that affect the outcome of minimally invasive surgical procedures. One of the causes is attributed to accidental damages to arteries or veins, and one of the possible risk factors falls on the surgeon's skills. This paper presents the development and application of an Enhanced Vision System for Robotic Surgery (EnViSoRS), based on a user-defined Safety Volume (SV) tracking to minimize the risk of intraoperative bleeding. It aims at enhancing the surgeon's capabilities by providing Augmented Reality (AR) assistance toward the protection of vessels from injury during the execution of surgical procedures with a robot. The core of the framework consists in (i) a hybrid tracking algorithm (LT-SAT tracker) that robustly follows a user-defined Safety Area (SA) in long term; (ii) a dense soft tissue 3D reconstruction algorithm, necessary for the computation of the SV; (iii) AR features for visualization of the SV to be protected and of a graphical gage indicating the current distance between the instruments and the reconstructed surface. EnViSoRS was integrated with a commercial robotic surgical system (the dVRK system) for testing and validation. The experiments aimed at demonstrating the accuracy, robustness, performance, and usability of EnViSoRS during the execution of a simulated surgical task on a liver phantom. Results show an overall accuracy in accordance with surgical requirements (<5 mm), and high robustness in the computation of the SV in terms of precision and recall of its identification. The optimization strategy implemented to speed up the computational time is also described and evaluated, providing AR features update rate up to 4 fps, without impacting the real-time visualization of the stereo endoscopic video. Finally, qualitative results regarding the system usability indicate that the proposed system integrates well with the commercial surgical robot and has indeed potential to offer useful assistance during real surgeries.
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