Developing robotic tools that introduce substantial changes in the surgical workflow is challenging because quantitative requirements are missing. Experiments on cadavers can provide valuable information to derive workspace requirements, tool size, and surgical workflow. This work aimed to quantify the volume inside the knee joint available for manipulation of minimally invasive robotic surgical tools. In particular, we aim to develop a novel procedure for minimally invasive unicompartmental knee arthroplasty (UKA) using a robotic laser-cutting tool. Methods: Contrast solution was injected into nine cadaveric knees and computed tomography scans were performed to evaluate the tool manipulation volume inside the knee joints. The volume and distribution of the contrast solution inside the knee joints were analyzed with respect to the femur, tibia, and the anatomical locations that need to be reached by a laser-cutting tool to perform bone resection for a standard UKA implant. Results: Quantitative information was determined about the tool manipulation volume inside these nine knee joints and its distribution around the cutting lines required for a standard implant. Conclusion: Based on the volume distribution, we could suggest a possible workflow for minimally invasive UKA, which provides a large manipulation volume, and deducted that for the proposed workflow, an instrument with a thickness of 5-8 mm should be feasible. Significance: We present quantitative information on the three-dimensional distribution of the maximally available volume inside the knee joint. Such quantitative information lays the basis for developing surgical tools that introduce substantial changes in the surgical workflow.

To overcome the physical limitations of mechanical bone cutting in minimally invasive surgery, we are developing a miniature parallel robot that enables positioning of a pulsed laser with an accuracy below 0.25 mm and minimizes the required manipulation space above the target tissue. This paper presents the design, control, device characteristics, functional testing, and performance evaluation of the robot. The performance of the robot was evaluated within the scope of a path-following experiment. The required accuracy for continuous cuts was achieved and reached 0.176 mm on the test bench.

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Redundant robots allow multiple robot joint configurations for the same end-effector pose by moving only in null space. Robot's motions in null space are not intuitive to predict in general and in particular for medical personnel. In this work, we present a control concept that allows the operator to focus on the correct end-effector pose during time-critical tasks, e.g. change of the endoscope pose during a surgical intervention, while the shape of the redundant robotic structure is handled autonomously based on previously learnt preferred shapes close to the actual end-effector pose. We investigated the benefit of the proposed learned task space control over naive task space control that required an operator to manually control a virtual robot in task space and null space independently. In a first user study, we found that learned task space control significantly reduced the effort -as measured by task duration and task load -for operators compared to naive task space control.