Bony free flap reconstruction of the facial skeleton remains a challenging area of reconstructive surgery. Despite technological advances that have aided planning and execution of these procedures, surgical inaccuracy is not insignificant. One source of error that has not been wholly addressed is that attributable to a human operator. In this study, we investigate the feasibility and accuracy of performing osteotomies robotically in pre-programmed fashion for fibula free flap mandible reconstruction as a method to reduce inaccuracies related to human error. A mandibular defect and corresponding free fibula flap reconstruction requiring six osteotomies were designed on a CAD platform. A methodology was developed to translate this virtual surgical plan data to a robot (KUKA, Augsburgs, Germany), which then executed osteotomies on three-dimensional (3D) printed fibula flaps with the aid of dynamic stereotactic navigation. Using high-resolution computed tomography, the osteotomized segments were compared to the virtually planned segments in order to measure linear and angular accuracy. A total of 18 robotic osteotomies were performed on three 3D printed fibulas. Compared to the virtual preoperative plan, the average linear variation of the osteotomized segments was 1.3 ± 0.4 mm, and the average angular variation was 4.2 ± 1.7°. This preclinical study demonstrates the feasibility of pre-programmed robotic osteotomies for free fibula flap mandible reconstruction. Preliminarily, this method exhibits high degrees of linear and angular accuracy, and may be of utility in the development of techniques to further improve surgical accuracy.
Abstract-In present days, the number of application in which robots and users share the same workspace is increasing, as long as the need of cooperation between them. To achieve a smooth cooperation, in particular in surgical applications, the robot needs to timely change its behavior to adapt to the needs of the user.In this work, a simplified scenario for neurosurgery was defined in which the user interacts with the robot through a Graphical User Interface (GUI) and by touching the robot links and, based to those events and on the current status, different control modes are enabled in the high level controller we developed, such as autonomous, cooperative and teleoperation.Experiments were performed to measure the performances and safety of the developed high level controller in handling the transitions between two states by checking the continuity of data from the robot and from an external measurement system.Results proved that the trajectories of the end effector and links during the switching phase are continuous and thus the modular high level controller developed switches control safely without undesired deviation from desired course.
For achieving dynamic manipulation capabilities that are comparable to human performance in terms of speed, energetic properties, and robustness, intrinsic elasticity is widely proposed as a necessary robot design element. In this paper we show how passive compliance can be exploited for a 6-degree-of-freedom (DoF) cyclic ball dribbling task with a 7-DoF articulated Cartesian impedance controlled DLR Lightweight Robot III. For this, the robot is equipped with an elastic hand, which extends the contact time and therefore, also enlarges both, observability and controllability of the ball. We show via simulation and experiment that it is possible to achieve a stable dynamic cycle based on a 1 DoF analysis from [1] for the main axis together with control strategies for the secondary translations and rotations of the task. The scheme allows also the continuous tracking of a desired dribbling height and horizontal position. As a human is able to dribble blindly, we decided to solve the task by force sensing only, i.e. no vision is used for our approach, however, it could be easily incorporated.
In surgical procedures, robots can accurately position and orient surgical instruments. Intraoperatively, external sensors can localize the instrument and compute the targeting movement of the robot, based on the transformation between the coordinate frame of the robot and the sensor. This paper addresses the assessment of the robustness of an iterative targeting algorithm in perturbed conditions. Numerical simulations and experiments (with a robot with seven degrees of freedom and an optical tracking system) were performed for computing the maximum error of the rotational part of the calibration matrix, which allows for convergence, as well as the number of required iterations. The algorithm converges up to 50 degrees of error within a large working space. The study confirms the clinical relevance of the method because it can be applied on commercially available robots without modifying the internal controller, thus improving the targeting accuracy and meeting surgical accuracy requirements.
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