One issue of robotic microsurgery is that compared to manual surgery, the operation time tends to be longer due to high motion scaling. To address this issue, we developed a new controller that can provide the accuracy required for microsurgery without a high scaling factor by utilizing fingertip and wrist motions. Also, for the better outcome of surgery, the proposed controller has a force feedback function which is not available for the existing controllers for microsurgical robots. A challenge of designing such a controller is associated with the size requirement. For conventional microsurgery, surgeons perform surgical procedures while looking at the eyepieces of a surgical microscope and the same applies for robotic microsurgery. The only space available to manipulate controllers is a narrow space between the patient/surgical bed and the surgeon. To satisfy this constraint, the proposed controller is integrated with a handrest and the controller’s DOFs are strategically allocated. In this work, as the first step of addressing the issue of prolonged operational time, we built a prototype controller and evaluated the accuracy and task space with simulations. The results indicated that by using the fingertip and wrist motions with a scaling factor of 3x, 0.5 mm diameter circles could be traced with a mean bidirectional precision of 0.0485 mm. Also, 10.0 mm diameter circles were traceable with the same scaling factor.

When performing some surgical tasks inside colon with NOTES technology, colon tissue could block the task space and occlude the endoscopic vision. In order to solve this problem, we developed a pneumatically driven deployable and undeployable structure which can distend collapsing tissue and can be delivered through a 4.5 mm endoscopic channel. The structure is designed to be flexible enough to pass through colon's tortuous pathway. Also, it is designed to hold its shape without continually applying air pressure after deployment. This allows to make use of an endoscopic channel for the other surgical instruments. Besides, due to the compliant nature of the device, it is safe to deploy inside a smaller space than its maximum deployable size. The functionality of the device was verified with an in-vitro experiment. The structure was successfully deployed inside a pig's colon with an inner diameter of 60 mm by applying 3.5 bars of air pressure and created a sufficient task space for surgical operations.

Minimally Invasive Surgery (MIS) can reduce iatrogenic injury and decrease the possibility of surgical complications. This paper presents a novel flexible and bendable endoscopic device, “Roboscope”, which delivers two instruments, two miniature scanning fiber endoscopes, and a suction/irrigation port to the operation site through a single portal. Compared with existing bendable and steerable robotic surgical systems, Roboscope provides two bending degrees of freedom for its outer sheath and two insertion degrees of freedom, while simultaneously delivering two instruments and two endoscopes to the surgical site. Each bending axis and insertion freedom of Roboscope is independently controllable via an external actuation pack. Surgical tools can be changed without retracting the robot arm. This paper presents the design of the Roboscope mechanical system, electrical system, and control and software systems, design requirements and prototyping validation as well as analysis of Roboscope workspece.

Beside the output-input hysteresis, the longitudinally loaded cables of medical robotics such as RAVEN II exhibit asymmetric saturated strain-load hysteresis loops. This study investigates modeling the hysteresis nonlinearities of these cables using a stop-operator based Prandtl-Ishlinskii (SPI) model that is integrated with a memoryless function. The stop-operator based model is employed to account for the hysteresis nonlinearities, while the memoryless function is introduced to characterize saturation and asymmetric effects. A numerical example is presented to compare the properties of the proposed model with the classic SPI model. The response of the suggested model was evaluated on the hysteresis properties of two different cables subjected to triangular harmonic input of 0 to 0.001 with 6.25 × 10-5strain/s. The characterization error of the thick cable was found as 1.55 %, while the error was calculated as 1.25 % for the thin cable. The relative significance of the proposed model was further examined by comparing the measured data with the classic SPI model. The results showed that the classic model yields substantial characterization errors when the asymmetry and saturation effects of the strain-load hysteresis loops are ignored.

Surgical robot research is driven by the desire of improving surgical outcomes. This paper proposed a Recurrent Neural Network based controller to address two problems: 1) improving control precision, 2) increasing adaptiveness for robot motion (explained in Section I). RNN was adopted in this work mainly because 1) the problem formulation naturally matches RNN structure, 2) RNN has advantages as an biologically inspired method. The proposed method was explained in detail and analysis shows that the proposed method is able to dynamically regulate outputs to increase the adaptiveness and the control precision. This paper uses Raven II surgical robot as an example to show the application of the proposed method, and the numeral simulation results from the proposed method and three other controllers show that the proposed method has improved precision, improved high robustness against noise and increased movement smoothness, and it keeps the manipulator links as far away as possible from physical boundaries, which potentially increases surgical safety and leads to improved surgical outcomes.

Cable driven manipulators are popular in surgical robots due to compact design, low inertia, and remote actuation. In these manipulators, encoders are usually mounted on the motor, and joint angles are estimated based on transmission kinematics. However, due to non-linear properties of cables such as cable stretch, lower stiffness, and uncertainties in kinematic model parameters, the precision of joint angle estimation is limited with transmission kinematics approach. To improve the positioning of these manipulators, we use a pair of low cost stereo camera as the observation for joint angles and we input these noisy measurements into an Unscented Kalman Filter (UKF) for state estimation. We use the dual UKF to estimate cable parameters and states offline. We evaluated the effectiveness of the proposed method on a Raven-II experimental surgical research platform. Additional encoders at the joint output were employed as a reference system. From the experiments, the UKF improved the accuracy of joint angle estimation by 33- 72%. Also, we tested the reliability of state estimation under camera occlusion. We found that when the system dynamics is tuned with offline UKF parameter estimation, the camera occlusion has no effect on the online state estimation.

Haptic feedback plays a key role in surgeries, but it is still a missing component in robotic Minimally Invasive Surgeries. This paper proposes a dynamic model-based sensorless grip force estimation method to address the haptic perception problem for commonly used elongated cable-driven surgical instruments. Cable and cable-pulley properties are studied for dynamic modeling; grip forces, along with driven motor and gripper jaw positions and velocities are jointly estimated with Unscented Kalman Filter and only motor encoder readings and motor output torques are assumed to be known. A bounding filter is used to compensate for model inaccuracy and to improve method robustness. The proposed method was validated on a 10mm gripper which is driven by a Raven-II surgical robot. The gripper was equipped with 1-dimensional force sensors which served as ground truth data. The experimental results showed that the proposed method provides sufficiently good grip force estimation, while only motor encoder and the motor torques are used as observations.

In this paper, we propose model of longitudinally loaded cable based on the Bouc-Wen hysteresis model and within the framework of the Duhem operator. By optimizing the 9 hysteresis model parameters with a genetic algorithm, the proposed model is shown to be capable of representing quasi-static response of two different diameter cables, 0.61 mm (thin) and 1.19 mm (thick), used for the RAVEN II surgical robotic surgery platform. The construction of the cable is 7 strands with 19 individual wires per strand. Furthermore, it is shown that the dynamic response of the cables are captured by adding a linear damping term. The hysteresis model and linear damper with the optimized parameters accurately models a longitudinal vibration test result in terms of frequency, steady state stretch, and logarithmic decrement. Energy dissipation due solely to the hysteresis term is approximately calculated to be 57 and 71% of the total energy loss for the thin and thick cables respectively. The proposed model may be used for cables with different contraction and diameter and can be applied for control of cable driven robots in which cables are stretched longitudinally without large excitation of other modes.

Cable driven power transmission is popular in many manipulator applications including medical arms. In spite of advantages obtained by removing motors from the mechanism, cable transmission introduces higher non-linearity and more uncertainties such as cable stretch and cable coupling. In order to improve the control precision and robustness of the Raven-II surgical robot, particularly for automation applications, the Unscented Kalman Filter (UKF) was adopted for state estimation. The UKF estimated state variables of the Raven-II dynamic model from sensor data. The dual UKF was used offline to estimate cable coupling parameters. The experimental results showed that the proposed method improved joint position estimation precision and the estimation consistency, especially on the more elastic links. The improvements for links 2 and 3 of the Raven were 36.76%, and 62.99%, respectively. For link 1 the improvement was 1.43% because the transmission is very stiff.

In this paper we present experimentally obtained cable-pulley Coulomb and viscous friction for cable-driven surgical robotic systems including the RAVEN II surgical robotic research platform. In the study of controlling cable-driven systems a simple mathematical model which does not capture physical behavior well is often employed. Even though control of such systems is achievable without an accurate model, fully understanding the behavior of the system will potentially realize more robust control. A surgical robot is one of the systems that often relies on cables as an actuation method as well as pulleys to guide them. Systems with such structure encounter frictional force related to conditions of cable and pulley such as cable velocity, tension, type and number of pulley, and angle of cable wrapping around pulley. Using a couple of test platforms that incorporate cable, pulleys, and other experimental conditions corresponding to the RAVEN II system, it is shown that cable-pulley friction is function of tension, wrap angle, and number of pulleys and not of magnitude of cable velocity.