A robotic system for solo surgery in flexible ureteroscopy: development and evaluation with clinical users.

PURPOSE: The robotic system CoFlex for kidney stone removal via flexible ureteroscopy (fURS) by a single surgeon (solo surgery, abbreviated SSU) is introduced. It combines a versatile robotic arm and a commercially available ureteroscope to enable gravity compensation and safety functions like virtual walls. The haptic feedback from the operation site is comparable to manual fURS, as the surgeon actuates all ureteroscope DoF manually. METHODS: The system hardware and software as well as the design of an exploratory user study on the simulator model with non-medical participants and urology surgeons are described. For each user study task both objective measurements (e.g., completion time) and subjective user ratings of workload (using the NASA-TLX) and usability (using the System Usability Scale SUS) were obtained. RESULTS: CoFlex enabled SSU in fURS. The implemented setup procedure resulted in an average added setup time of 341.7 ± 71.6 s, a NASA-TLX value of 25.2 ± 13.3 and a SUS value of 82.9 ± 14.4. The ratio of inspected kidney calyces remained similar for robotic (93.68 %) and manual endoscope guidance (94.74 %), but the NASA-TLX values were higher (58.1 ± 16.0 vs. 48.9 ± 20.1) and the SUS values lower (51.5 ± 19.9 vs. 63.6 ± 15.3) in the robotic scenario. SSU in the fURS procedure increased the overall operation time from 1173.5 ± 355.7 s to 2131.0 ± 338.0 s, but reduced the number of required surgeons from two to one. CONCLUSIONS: The evaluation of CoFlex in a user study covering a complete fURS intervention confirmed the technical feasibility of the concept and its potential to reduce surgeon working time. Future development steps will enhance the system ergonomics, minimize the users' physical load while interacting with the robot and exploit the logged data from the user study to optimize the current fURS workflow.

A Digital Twin Approach for Contextual Assistance for Surgeons During Surgical Robotics Training.

Minimally invasive robotic surgery copes with some disadvantages for the surgeon of minimally invasive surgery while preserving the advantages for the patient. Most commercially available robotic systems are telemanipulated with haptic input devices. The exploitation of the haptics channel, e.g., by means of Virtual Fixtures, would allow for an individualized enhancement of surgical performance with contextual assistance. However, it remains an open field of research as it is non-trivial to estimate the task context itself during a surgery. In contrast, surgical training allows to abstract away from a real operation and thus makes it possible to model the task accurately. The presented approach exploits this fact to parameterize Virtual Fixtures during surgical training, proposing a Shared Control Parametrization Engine that retrieves procedural context information from a Digital Twin. This approach accelerates a proficient use of the robotic system for novice surgeons by augmenting the surgeon's performance through haptic assistance. With this our aim is to reduce the required skill level and cognitive load of a surgeon performing minimally invasive robotic surgery. A pilot study is performed on the DLR MiroSurge system to evaluate the presented approach. The participants are tasked with two benchmark scenarios of surgical training. The execution of the benchmark scenarios requires basic skills as pick, place and path following. The evaluation of the pilot study shows the promising trend that novel users profit from the haptic augmentation during training of certain tasks.

Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases.

Certain telerobotic applications, including telerobotics in space, pose particularly demanding challenges to both technology and humans. Traditional bilateral telemanipulation approaches often cannot be used in such applications due to technical and physical limitations such as long and varying delays, packet loss, and limited bandwidth, as well as high reliability, precision, and task duration requirements. In order to close this gap, we research model-augmented haptic telemanipulation (MATM) that uses two kinds of models: a remote model that enables shared autonomous functionality of the teleoperated robot, and a local model that aims to generate assistive augmented haptic feedback for the human operator. Several technological methods that form the backbone of the MATM approach have already been successfully demonstrated in accomplished telerobotic space missions. On this basis, we have applied our approach in more recent research to applications in the fields of orbital robotics, telesurgery, caregiving, and telenavigation. In the course of this work, we have advanced specific aspects of the approach that were of particular importance for each respective application, especially shared autonomy, and haptic augmentation. This overview paper discusses the MATM approach in detail, presents the latest research results of the various technologies encompassed within this approach, provides a retrospective of DLR's telerobotic space missions, demonstrates the broad application potential of MATM based on the aforementioned use cases, and outlines lessons learned and open challenges.