Robotic ultrasound (US) systems represent an emerging frontier in medical imaging. A fundamental component of these systems is the rigid body transformation between the robot flange and the attached US probe, which enables mapping of visual data from image space to the robot's reference frame. Traditionally, calibrating this transformation has been a tedious process, complicated by equipment demands and operational constraints arising from the probe's narrow field of view. This work presents a novel calibration strategy based on conic sections geometry, which offers several key simplifications over existing approaches: 1). It requires no external equipment beyond a single cone phantom; 2). It operates with a small input size and imposes no strict alignment or motion constraints on the US scan plane during calibration; and 3). It employs a straightforward pattern analysis pipeline to process images acquired from phantom scans. Experimental validation results show that the proposed method achieves accuracy comparable to existing state-of-the-art approaches while delivering superior precision, thereby demonstrating enhanced calibration reproducibility enabled by its streamlined workflow. These advantages make this method particularly suitable for application in clinical scenarios that require frequent and efficient calibration.

Magnetic compression anastomosis (MCA) offers a promising solution for minimally invasive anastomosis surgery. However, current MCA schemes lack safe, real-time localization and guidance for compression magnets, hindering surgeons' ability to control the compression magnets effectively in complex, unstructured endoluminal environments. To address these limitations, this paper introduces the MagsL-HUD endoscopic system, a novel solution that enables multi-magnetic six-degree-of-freedom (six-DoF) localization and head-up display (HUD) guidance within the endoscopic view (EV). Specifically, the system integrates a developed Endo-MagCap device with an orthogonal magnet configuration, along with a magnetic sensor array, to achieve real-time full-pose localization. An endoscopic camera model is incorporated for HUD visualization, enhancing intuitive interaction for surgeons' better-informed decisions. Eventually, the effectiveness of the MagsL-HUD endoscopic system is validated through laboratory experiments andex vivoanimal trials. The system demonstrates six-DoF tracking accuracy with average errors of 0.0070 m and 0.1437 rad, and 0.0071 m and 0.1721 rad in the designed trajectory cases for two compression magnets, respectively. Additionally,ex vivoporcine tests confirm the system's feasibility and applicability, successfully performing a stomach-colon MCA surgery with a final compression gap of approximately 0.00247 m. Further comparative studies demonstrate that the MagsL-HUD method has a compression success rate of 71.4$\%$versus 42.9$\%$of the non-HUD approaches in the designed tests. This work represents a significant step toward the clinical adoption of magnetic-assisted endoscopy for minimally invasive anastomosis surgeries, holding substantial practical significance for improving the safety and efficacy of MCA procedures in complex, unstructured endoluminal environments.

Endoscopic submucosal dissection (ESD) is a procedure targeted for early gastrointestinal cancer. Traction plays a crucial role in enhancing the efficiency of cutting lesions, thereby reducing procedural complexity and duration. From the perspective of traction devices, current non-magnetic ones hold shortcomings in complicating the workspace in directional tissue manipulation; Current magnetic traction devices cannot be prepared before the procedure, and require the withdrawal of endoscope in the midway to re-introduce the magnetic retractor to the lesion site. Towards these plights, this paper introduces a robotic flexible magnetic retractor designed for tissue manipulation during ESD. Precisely, the flexible prototype can be seamlessly inserted through the instrument channel of an endoscope to the lesion site without the need for endoscope withdrawal. Moreover, the introduction of robotic magnetic actuation enhances the agile control of magnetic retractors while alleviating the surgeon's workload in magnetic-retractor-assisted ESD. The experimental results validate the functionality and efficacy of the prototype magnetic retractor in magnetic traction-assisted ESD procedures. The retractor demonstrated its ability to provide adequate traction and accomplish clinical tasks. This innovative approach holds promise for enhancing the efficiency and outcomes of ESD procedures, offering a compelling alternative to traditional traction methods.

Magnetically actuated capsule endoscopic robots (MACERs) are becoming increasingly popular because they can reach deep diseased regions inside the body that are difficult or inaccessible to traditional endoscopes without the restriction of mechanical transmission medium. However, MACERs are highly nonlinear, hence achieving obstacle avoidance, safe, and stable target tracking control of MACERs remains a challenging research topic. Therefore, to satisfy the diagnosis and treatment needs of the deep diseased regions inside the body, this paper designs a MACER target tracking neural network control method with obstacle avoidance and noise-resistant capabilities. Firstly, the kinematics and obstacle avoidance model of the MACER are established, and then a moving target tracking control scheme of robot with joint motion constraints and obstacle avoidance capabilities is designed. Next, a noise-resistant neural network is designed to quickly solve the MACER’s control scheme, thereby achieving safe, obstacle avoidance, and stable target tracking control of the MACER. Finally, the effectiveness and practicability of the proposed method are checked by simulation analysis and experiment on MACER, and compared with the existing methods. The experimental results indicate that the neural network method proposed can effectively control the MACER to track the target motion along the gastric wall curve. Compared with existing methods, the designed method has stronger anti-noise interference ability, the convergence accuracy of the proposed method is improved by 1.3 times, and the computational burden is reduced by 26.7 times.

Despite advantages from neurosurgical systems, achieving intuitive and safe collaboration with robot during the coarse positioning of instrument insertion end effector (IIEE) remains a critical issue. In this paper, we propose a novel non-contact hand-guided method for such advancement based on magnetic sensing. First, a wearable magnet band and a magnetic sensor are designed, based on which the magnetic localization is achieved for surgeon’s hand location detection. Second, a quadratic programming-based control is implemented, to guarantee the pose-based servo performance, higher rotational manipulability for IIEE fine alignment, and joint position&velocity limits avoidance. For evaluation, two experiments are designated and conducted. Results show that the magnetic localization algorithm can achieve < 4.7 mm and 2.6° errors in a dynamic path tracking test, which can provide an accurate magnet location for hand guidance. Moveover, workflow of the proposed solution in a brain biopsy scenario demonstrates its enhancement of IIEE rotational manipulability (11.6% increase at final configuration), and safety improvement of collision avoidance when other surgeon approaches for cannula delivery. This research contributes to enhanced intuitiveness and safety for surgeon-robot collaborative coarse positioning of IIEE in neurosurgery.

In robotic teleoperation systems, the effectiveness of teleoperation relies heavily on the operator performing control actions, underscoring the importance of master device design. Breaking away from the mechanical framework that relies on complex structures and restricts workspace, this paper adopts a new magnetic method and introduces a wireless magnetic master device (MMD) with an expandable, singularity-free workspace, designed to enhance maneuverability and operational reach. Specifically, the concept and development of the MMD for robotic teleoperation are presented, followed by an exploration of key technical aspects, including a six-degree-of-freedom (DoF) tracking approach using dual magnetic localization and controller design for the robotic arm using the MMD. Finally, the proposed method’s feasibility and accuracy are validated through magnetic localization and teleoperation control tests. Results indicate that the MMD achieves six-DoF localization with an average Euclidean localization error ofet= 0.0018 m and an average Geodesic distance error ofeR= 0.0604 rad within the central region of the workspace, and six-DoF manipulation (velocityet= 0.0062 m andeR=0.2091 rad in tests. Furthermore, the overall teleoperation control framework achieves tracking accuracy withet= 0.0085 m andeR= 0.1475 rad in robotic calligraphy task; achieves a broad scanning range of 0.2746 m along they-axis in robotic ultrasound scanning task; achieves a large-angle rotation of 9.15 rad in robotic clamp rotating task. Overall, this research advances master device design, aiming to inspire further innovation in master-follower teleoperation control for human-machine systems.

In minimally invasive surgery (MIS), the field of view (FOV) control is crucial. Autonomous endoscope robots have been developed to facilitate MIS procedures by enabling autonomous surgical target tracking, thus reducing the workload on surgeons. However, existing visual servoing-based target tracking methods for autonomous endoscopes often overlook the insecurity stemming from restricted workspace conditions. Instances, such as collisions between the endoscope robot’s tip and the patient’s chest or abdominal wall pose risks to patient tissue, while extensive motion of the endoscope shaft may damage incision port tissue. Addressing these security concerns, this article proposes a novel approach called virtual fixture-based restricted workspace constraint (RWSC) to reconstruct the endoscope robot’s movement range. A quadratic programming (QP) optimization framework is employed to govern the robot’s motion, ensuring autonomous target tracking while adhering to RWSCs. To solve the QP problem, we propose an adaptive zeroing neural network (ZNN) featuring a newly designed activation function (AF). This AF enhances the ZNN with predefined-time convergence and noise rejection capabilities, making it especially suitable for time-sensitive and noise-prone surgical applications. Theoretical analysis and experimental results demonstrate that our adaptive ZNN achieves shorter convergence times than existing neural dynamic-based QP solvers. Physical validations show the efficacy of the proposed RWSCs in limiting the workspace of the endoscope robot, while the FOV control strategy enables autonomous target tracking of flexible endoscopes under diverse constraints and objectives.

In response to torso-oriented magnetic localization tasks that require the system to have interactivity and flexibility with guaranteed accuracy, a novel bio-inspired magnetic sensor array configuration is proposed in this paper. Precisely, the ideas of the natural characteristics of octopus flexible tentacles and the "wrap" morphology are integrated into the design of the magnetic localization system based on the sensor array method. It is worth mentioning that such a design enhances the interactivity and flexibility of the localization system compared to the general planar sensor array strategy. Apart from the concept introduction, the geometry analysis of the proposed configuration is presented based on the constant curvature model. Besides, the magnetic localization algorithm for the system is presented by constructing a magnetic tracking optimization function. Eventually, the proposed concept and developed algorithm are examined in the sensor-array-simulation environment to manifest their effectiveness and applicability. The experimental results indicate that the octopus-inspired-configuration sensor array achieves a mean accuracy at a centimeter-level in our cases, and has better accuracy with a mean value of ē as 0.0178 m and ${\overline {SQR} _{ave{\text{ }}}}$ as 0.0883 for the center interest space compared to general planar configuration one. Moreover, the effect of the configuration error is analyzed. These results verify the feasibility and superiority of the proposed concept and hold significant practical significance in addressing the challenge associated with magnetic localization tasks toward the clinical application scenarios.

This paper is concerned with the issue of the kinematic model-based bending control for the magnetically actuated robotic endoscope and its application for automatic retroflexion. By the utilization of the Cosserat rod theory and the transformation in the magnetic tip of the endoscope, the comprehensive kinematic model of the magnetically-actuated robotic endoscope is established. Afterward, a magnetic control scheme for the bending motion is proposed by co-developing an error feedback PID control strategy and the model-based feedback approach. Moreover, as one unique kind of bending motion, retroflexion is taken into account, and the strategy aimed at the bid of compact space retroflexion is presented by virtue of the introduction of serial waypoints pursuing the position of the magnetic tip being close to the midline as possible. Eventually, the developed modeling and bending control scheme and the compact space retroflexion strategy are examined in a magnetically actuated robotic endoscope system to manifest the effectiveness and applicability of the theoretical approach. The experimental results indicate that the designed controller can drive the endoscope to bend to the desired pose and show a reduction of about 47.01% in the sweeping area and 79.25% in the last distance to midline achieved by conducting compact space retroflexion in comparison to “U” type one.

This paper is concerned with the issue of bumpless transfer control for a class of hybrid stochastic systems with a stochastic switching rule. The switching rule is regarded as a hidden semi-Markov switching process by utilizing concepts of emission probability and semi-Markov kernel. In light of the mismatching of mode observation happening in the operating procedure of subsystem, comprehensive bumpless transfer constraints that not only work on the switching instants but also the sojourn process, are proposed. On the basis of the mean-square stability criteria and comprehensive bumpless transfer constraints, numerically testable conditions are established to obtain the stabilizing state-feedback controller with bumpless transfer performance by introducing some mathematical techniques. The theoretical results are testified by a switched RLC electromagnetic oscillation circuit to demonstrate the effectiveness of the designed control strategy.