Kinematic optimization for the design of a collaborative robot end-effector for tele-echography

Tele-examination based on robotic technologies is a promising solution to solve the current worsening shortage of physicians. Echocardiography is among the examinations that would benefit more from robotic solutions. However, most of the state-of-the-art solutions are based on the development of specific robotic arms, instead of exploiting COTS (commercial-off-the-shelf) arms to reduce costs and make such systems affordable. In this paper, we address this problem by studying the design of an end-effector for tele-echography to be mounted on two popular and low-cost collaborative robots, i.e., the Universal Robot UR5, and the Franka Emika Panda. In the case of the UR5 robot, we investigate the possibility of adding a seventh rotational degree of freedom. The design is obtained by kinematic optimization, in which a manipulability measure is an objective function. The optimization domain includes the position of the patient with regards to the robot base and the pose of the end-effector frame. Constraints include the full coverage of the examination area, the possibility to orient the probe correctly, have the base of the robot far enough from the patient’s head, and a suitable distance from singularities. The results show that adding a degree of freedom improves manipulability by 65% and that adding a custom-designed actuated joint is better than adopting a native seven-degrees-freedom robot

Development of a cognitive robotic system for simple surgical tasks

The introduction of robotic surgery within the operating rooms has significantly improved the quality of many surgical procedures. Recently, the research on medical robotic systems focused on increasing the level of autonomy in order to give them the possibility to carry out simple surgical actions autonomously. This paper reports on the development of technologies for introducing automation within the surgical workflow. The results have been obtained during the ongoing FP7 European funded project Intelligent Surgical Robotics (I-SUR). The main goal of the project is to demonstrate that autonomous robotic surgical systems can carry out simple surgical tasks effectively and without major intervention by surgeons. To fulfil this goal, we have developed innovative solutions (both in terms of technologies and algorithms) for the following aspects: fabrication of soft organ models starting from CT images, surgical planning and execution of movement of robot arms in contact with a deformable environment, designing a surgical interface minimizing the cognitive load of the surgeon supervising the actions, intra-operative sensing and reasoning to detect normal transitions and unexpected events. All these technologies have been integrated using a component-based software architecture to control a novel robot designed to perform the surgical actions under study. In this work we provide an overview of our system and report on preliminary results of the automatic execution of needle insertion for the cryoablation of kidney tumours

APP-RUSS: Automated Path Planning for Robotic Ultrasound System

Autonomous robotic ultrasound System (RUSS) has been extensively studied. However, fully automated ultrasound image acquisition is still challenging, partly due to the lack of study in combining two phases of path planning: guiding the ultrasound probe to the scan target and covering the scan surface or volume. This paper presents a system of Automated Path Planning for RUSS (APP-RUSS). Our focus is on the first phase of automation, which emphasizes directing the ultrasound probe's path toward the target over extended distances. Specifically, our APP-RUSS system consists of a RealSense D405 RGB-D camera that is employed for visual guidance of the UR5e robotic arm and a cubic Bezier curve path planning model that is customized for delivering the probe to the recognized target. APP-RUSS can contribute to understanding the integration of the two phases of path planning in robotic ultrasound imaging, paving the way for its clinical adoption

Robot-Assisted Image-Guided Interventions

Image guidance is a common methodology of minimally invasive procedures. Depending on the type of intervention, various imaging modalities are available. Common imaging modalities are computed tomography, magnetic resonance tomography, and ultrasound. Robotic systems have been developed to enable and improve the procedures using these imaging techniques. Spatial and technological constraints limit the development of versatile robotic systems. This paper offers a brief overview of the developments of robotic systems for image-guided interventions since 2015 and includes samples of our current research in this field

Robot-Assisted Image-Guided Interventions

Image guidance is a common methodology of minimally invasive procedures. Depending on the type of intervention, various imaging modalities are available. Common imaging modalities are computed tomography, magnetic resonance tomography, and ultrasound. Robotic systems have been developed to enable and improve the procedures using these imaging techniques. Spatial and technological constraints limit the development of versatile robotic systems. This paper offers a brief overview of the developments of robotic systems for image-guided interventions since 2015 and includes samples of our current research in this field

Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.Comment: Accepted by Medical Image Analysi

Robotic Ultrasound Tomography and Collaborative Control

Ultrasound computed tomography (USCT) offers quantitative anatomical tissue characterization for cancer detection, and has shown similar diagnostic power to MRI on ex vivo prostate tissue. While most USCT research and commercial development has focused on submerging target anatomy in a transducer-lined cylindrical water-tank, this approach is not practical for imaging deep anatomy like the prostate and an alternative acquisition system using aligned abdominal and endolumenal ultrasound probes is required. This work outlines a clinical workflow, calibration scheme, and motion framework for an innovative dual-robotic USCT acquisition system specific to in vivo prostate imaging – one arm wielding a linear abdominal probe, the other wielding a linear transrectal ultrasound (TRUS) probe. After a three-way calibration, the robotic system works to autonomously keep the abdominal probe collinear with the physician-rotated TRUS probe using a hybrid force-position convex contour tracking scheme, while impedance control enforces its gentle contact with the patient’s pubic region for capturing the transmission ultrasound slices needed for limited-angle tomographic reconstruction. TRUS rotation was induced by joystick control for precision during testing, however collaborative control via admittance control of hand forces presents a useful workflow option to the physician. An improved robot admittance control algorithm for transparent collaborative control utilizing Kalman filtering was developed and verified to smooth robot hand guidance. Such an improvement additionally has important implications for generally alleviating ultrasonographer musculoskeletal strain through cooperatively controlled robots. The ultimate dual-robotic USCT system proved repeatable and sufficiently accurate for tomography based on pelvic phantom testing. Future steps in system verification and validation are discussed, as is incorporation into feasibility studies to test the potential and utility of the system for future prostate malignancy diagnosis and staging in vivo

CO-ROBOTIC ULTRASOUND IMAGING: A COOPERATIVE FORCE CONTROL APPROACH

Ultrasound (US) imaging remains one of the most commonly used imaging modalities in medical practice due to its low cost and safety. However, 63-91% of ultrasonographers develop musculoskeletal disorders due to the effort required to perform imaging tasks. Robotic ultrasound (RUS), the application of robotic systems to assist ultrasonographers in ultrasound scanning procedures, has been proposed in literature and recently deployed in clinical settings using limited degree-of-freedom (DOF) systems. An example of this includes breast-scanning systems, which allow one-DOF translation of a large ultrasound array in order to capture patients’ breast scans and minimize sonographer effort while preserving a desired clinical outcome. Recently, the robotic industry has evolved to provide light-weight, compact, accurate, and cost-effective manipulators. We leverage this new reality in able to provide ultrasonographers with a full 6-DOF system that provides force assistance to facilitate US image acquisition. Admittance robot control allows for smooth human-machine interaction in a desired task. In the case of RUS, force control is capable of assisting sonographers in facilitating and even improving the imaging results of typical procedures. We propose a new system setup for collaborative force control in US applications. This setup consists of the 6-DOF UR5 industrial robot, and a 6-axes force sensor attached to the robot tooltip, which in turn has an US probe attached to it through a custom-designed probe attachment mechanism. Additionally, an independent one-axis load cell is placed inside this attachment device and used to measure the contact force between the probe and the patient’s anatomy in real time and independent of any other forces. As the sonographer guides the US probe, the robot collaborates with the hand motions, following the path of the user. When imaging, the robot can offer assistance to the sonographer by augmenting the forces applied by him or her, thereby lessening the physical effort required as well as the resulting strain. Additional benefits include force and velocity limiting for patient safety and robot motion constraints for particular imaging tasks. Initial results of a conducted user study show the feasibility of implementing the presented robot-assisted system in a clinical setting

Collaborative Surgical Robots:Optical Tracking During Endovascular Operations

Endovascular interventions usually require meticulous handling of surgical instruments and constant monitoring of the operating room workspace. To address these challenges, robotic- assisted technologies and tracking techniques are increasingly being developed. Specifically, the limited workspace and potential for a collision between the robot and surrounding dynamic obstacles are important aspects that need to be considered. This article presents a navigation system developed to assist clinicians with the magnetic actuation of endovascular catheters using multiple surgical robots. We demonstrate the actuation of a magnetic catheter in an experimental arterial testbed with dynamic obstacles. The motions and trajectory planning of two six degrees of freedom (6-DoF) robotic arms are established through passive markerguided motion planning. We achieve an overall 3D tracking accuracy of 2.3 ± 0.6 mm for experiments involving dynamic obstacles. We conclude that integrating multiple optical trackers with the online planning of two serial-link manipulators is useful to support the treatment of endovascular diseases and aid clinicians during interventions

The ARMM System-Autonomous Steering of Magnetically-Actuated Catheters:Towards Endovascular Applications

Positioning conventional endovascular catheters is not without risk, and there is a multitude of complications that are associated with their use in manual surgical interventions. By utilizing surgical manipulators, the efficacy of remote-controlled catheters can be investigated in vivo. However, technical challenges, such as the duration of catheterizations, accurate positioning at target sites, and consistent imaging of these catheters using non-hazardous modalities, still exist. In this paper, we propose the integration of multiple sub-systems in order to extend the clinical feasibility of an autonomous surgical system designed to address these challenges. The system handles the full synchronization of co-operating manipulators that both actuate a clinical tool. The experiments within this study are conducted within a clinically-relevant workspace and inside a gelatinous phantom that represents a life-size human torso. A catheter is positioned using magnetic actuation and proportional-integral (PI) control in conjunction with real-time ultrasound images. Our results indicate an average error between the tracked catheter tip and target positions of 2:09 0:49 mm. The median procedure time to reach targets is 32:6 s. We expect that our system will provide a step towards collaborative manipulators employing mobile electromagnets, and possibly improve autonomous catheterization procedures within endovascular surgeries