Accurate needle insertion is an important task in many medical procedures. This paper studies the case of an autonomous needle insertion system for central venous access, which is a risky and challenging procedure involving the simultaneous manipulation of an ultrasound probe and of a catheterization needle. The goal of this medical operation is to provide access to a deep central vein, which is a key step in cardiovascular treatments or for the administration of drugs and treatments for cancer or infections. Accordingly, in this work we propose an autonomous dual-arm system for central venous access. The system is composed of two Franka robotic arms that are precisely co-registered and collaborate to achieve accurate needle insertion by combining ultrasound and bioimpedance sensing to ensure robust deep vessels visualization and venipuncture detection. The proposed system performance is evaluated on a phantom trainer through experiments simulating the jugular vein access for cardiac catheterization purposes. Quantitative results show the system is able to autonomously scan the area of interest, localize the vein and perform autonomous needle insertion with high accuracy and placement error below 1.7mm, proving the potential of the technology for real clinical use.

Augmented reality (AR) is considered one of the most promising solutions for safer procedures in several surgical specialities. Fusing patient-specific pre-operative information, typically 3D models extracted from CT scans or MRI, with real-time surgical images allows the surgeon to have detailed information on the anatomical structure of the surgical target intra-operatively. The coupling of AR and Robotics represents the next step towards introducing awareness into the surgical room, thus enhancing the surgeon's perceptual, cognitive and manipulative capabilities. This paper presents a novel integrated system for real-time AR navigation in robotic minimally invasive surgery (RMIS), composed of a robotic endoscopic camera, a robotic teleoperation implementing a software-based Remote Center of Motion (RCM), and an AR navigation software based on an initial manual registration of virtual 3D models with the real anatomy. The integrated system, as well as the individual modules, were evaluated in simulated surgical-like setups for accuracy and repeatability. The proposed system can perform high-precision tasks (position accuracy around$1 mm$and AR error lower than 7%), showing potential for application in different surgical procedures and setting the basis for autonomous robotic surgery operations.

Endoscopic laser tools have been recently proposed in order to overcome the limitations of state-of-the-art laser tools, by integrating fiber-coupled lasers into flexible endoscopic systems. One of the main challenges in designing such endoscopic tools consists in the focusing of the laser, that requires to be frequently adjusted reducing the reliability of the system and increasing surgeons’ mental workload. To avoid these problems, compact auto-focusing tools have been recently developed, taking advantage of MEMS varifocal mirrors (VM) to allow integration with endoscopic tools. In this paper, we integrate such VM-based tool with a distance sensing algorithm based on 3D surface reconstruction to achieve a complete autofocusing system. We evaluate the performance of the proposed integrated system by ablating lines on plaster block targets at variable distance and comparing the obtained ablation depth and width with that of a fixed focus system. Preliminary results show that the proposed system is able to keep the laser in focus resulting in uniform ablation lines for distance ranges from 14mm to 22mm.

Laser tattoo removal is a standard non-invasive method for removing color pigments on the skin. Increasing number of tattooed people who want to remove their tattoo has driven the medical laser market to develop new technologies for painless, scar-free and complete tattoo removal. However, manual use of such laser systems creates post-operative complications since they do not guarantee (i) protection on nontattooed skin from laser exposure, nor (ii) precise control of the laser focus during the operations for best performance. This paper introduces deTattoo, a robotic system to improve tattoo removal operations. A robotic arm is equipped with a RGB-D camera and a visible laser, in eye-in-end configuration. A hybrid visual servoing control is proposed to guarantee the correct pose of the laser with respect to the tattooed tissue while compensating body motions. 2D features tracked with a mass-spring-damper deformable mesh model are combined with the 3D reconstruction retrieved from a RGB-D camera in order to build the control law. Several experiments were conducted to evaluate the performance of the system with a fixed or moving tattooed surface, at different inclinations. Results showed that the proposed framework is able to fulfil the laser-based tattoo removal requirements, providing high positioning accuracy (<; 1mm) orientation (<; 0.2°) and body motion compensation.