An Open-Source Research Kit for the da Vinci ® Surgical System

Abstract-We present a telerobotics research platform that provides complete access to all levels of control via opensource electronics and software. The electronics employs an FPGA to enable a centralized computation and distributed I/O architecture in which all control computations are implemented in a familiar development environment (Linux PC) and lowlatency I/O is performed over an IEEE-1394a (FireWire) bus at speeds up to 400 Mbits/sec. The mechanical components are obtained from retired first-generation da Vinci R Surgical Systems. This system is currently installed at 11 research institutions, with additional installations underway, thereby creating a research community around a common open-source hardware and software platform

Accelerating Surgical Robotics Research: A Review of 10 Years With the da Vinci Research Kit

Robotic-assisted surgery is now well-established in clinical practice and has become the gold standard clinical treatment option for several clinical indications. The field of robotic-assisted surgery is expected to grow substantially in the next decade with a range of new robotic devices emerging to address unmet clinical needs across different specialities. A vibrant surgical robotics research community is pivotal for conceptualizing such new systems as well as for developing and training the engineers and scientists to translate them into practice. The da Vinci Research Kit (dVRK), an academic and industry collaborative effort to re-purpose decommissioned da Vinci surgical systems (Intuitive Surgical Inc, CA, USA) as a research platform for surgical robotics research, has been a key initiative for addressing a barrier to entry for new research groups in surgical robotics. In this paper, we present an extensive review of the publications that have been facilitated by the dVRK over the past decade. We classify research efforts into different categories and outline some of the major challenges and needs for the robotics community to maintain this initiative and build upon it

Design and Evaluation of a Performance-based Adaptive Curriculum for Robotic Surgical Training: A Pilot Study

Training with simulation systems has become a primary alternative for learning the fundamental skills of robotic surgery. However, there exists no consensus regarding a standard training curriculum: sessions defined a priori by expert trainers or self-directed by the trainees feature lack of consistency. This study proposes an adaptive approach that structures the curriculum on the basis of an objective assessment of the trainee's performance. The work comprised an experimental session with 12 participants performing training on virtual reality tasks with the da Vinci Research Kit surgical console. Half of the subjects self-managed their training session, while the others underwent the adaptive training. The final performance of the latter trainees was found to be higher compared to the former (p=0.002), showing how outcome-based, dynamic designs could constitute a promising advance in robotic surgical training

A progressive Cut Refinement Scheme for Revision Total Hip Replacement Surgery Using C-arm Fluoroscopy

Abstract. We describe a new method to cut a precise, high quality cavity in Revision Total Hip Replacement surgery (RTHR) using a set of intra-operative C-arm fluoroscopic images. With respect to previous approaches, our method provides the following new features: (1) a novel checkerboard plate was designed to correct the geometric distortion within fluoroscopic images. Unlike previous distortion correction devices, the plate doesn’t completely obscure any part of the image, and the distortion correction algorithm works well even when there are some overlaid objects in field of view; (2) a novel corkscrew fiducial object attached to the robot end-effector was designed, and a 6D pose estimation algorithm based on the 2D projection of the corkscrew is developed and used in robot-imager registration and imager co-registration; (3) we propose a progressive cut refinement scheme and an iterative cut location algorithm which utilizes image subtraction and 2D anatomy contour matching techniques. Several cutting experiments and some simulated experiments have been conducted to assess our techniques. The results indicate that our scheme is a promising method for RTHR application