The tendon-sheath mechanism (TSM) is widely used for flexible surgical robots owing to its ability to transfer motion through complicated paths and small volumes. However, precise motion control of the robots is difficult owing to the nonlinear characteristics of the TSM due to hysteresis, friction, deformation, backlash, etc. The hysteretic behavior exhibits a certain tendency depending on the shape of the TSM. In this study, our goal is to derive a hysteresis model that applies to the arbitrary geometry of a single-curve TSM. A hysteresis model was formulated by combining the Preisach hysteresis model, which has the structure of a weighted sum, and a recurrent neural network (RNN). Hysteresis output data were experimentally gathered for several representative shapes of the TSM to train the model. During data preprocessing, the data in the section where the hysteresis characteristic was prominent was augmented. Hyperparameter tuning using the grid search method was conducted to improve the performance of the model. The results indicate that the proposed model successively learned the tendency of configuration-specific hysteresis and adapted to arbitrary shapes of a single-curve TSM, even with shapes that the model did not learn.

Purpose: The current state of soft tissue surgery robots is surveyed, and the key technologies underlying their success are analyzed. State-of-the-art technologies are introduced, and future directions are discussed. Methods: Relevant literature is explored, analyzed, and summarized. Results: Soft tissue surgical robots had rapidly spread in the field of laparoscopic surgery based on the multi-degree-of-freedom movement of intra-abdominal surgical tools and stereoscopic imaging that are not possible in conventional surgery. The three key technologies that have made surgical robots successful are wire-driven mechanisms for multi-degree-of-freedom movement, master devices for intuitive remote control, and stereoscopic imaging technology. Recently, human-robot interaction technologies have been applied to develop user interfaces such as vision assistance and haptic feedback, and research on autonomous surgery has begun. Conclusion: Robotic surgery not only replaces conventional laparoscopic surgery but also allows for complex surgeries that are not possible with laparoscopic surgery. On the other hand, it is also criticized for its high cost and lack of clinical superiority or patient benefit compared to conventional laparoscopic surgery. As various robots compete in the market, the cost of surgical robots is expected to decrease. Surgical robots are expected to continue to evolve in the future due to the need to reduce the workload of medical staff and improve the level of care demanded by patients.

This paper presents a forward kinematic model of a wire-driven surgical robot arm with an articulated joint structure and path generation algorithms with solutions of inverse kinematics. The proposed methods were applied to a wire-driven surgical robot for single-port surgery. This robot has a snake-like robotic arm with double segments to fit the working space in a single port and a joint structure to secure stiffness. The accuracy of the model is highly important because small surgical robot arms are usually controlled by open-loop control. A curvature model is widely used to describe and control a continuum robotic body. However, the model is quite different from a continuum robotic arm with a joint structure and can lead to slack of the driving wires or decreased stiffness of the joints. An accurate forward kinematic model was derived to fit the actual hardware structure via the frame transformation method. An inverse kinematic model from the joint space to the wire-length space was determined from an asymmetric model for the joint structure as opposed to a symmetric curvature model. The path generation algorithm has to generate a command to send to each actuator in open-loop control. Two real-time path generation algorithms that solve for inverse kinematics from the task space to the joint space were designed and compared using simulations and experiments. One of the algorithms is an optimization method with sequential quadratic programming (SQP), and the other uses differential kinematics with a PID (Proportional-Integral-Derivative) control algorithm. The strengths and weaknesses of each algorithm are discussed.

Tendon sheath mechanism (TSM) is an essential mechanical element for the implementation of flexible endoscopic systems owing to its small volume and simple structure. However, nonlinear characteristics, such as backlash, hysteresis and friction occur when employing such a component. In this study, we formulate a Preisach hysteresis model consisting of elementary hysteresis operators. Subsequently, we propose a compensation algorithm that repeatedly and sequentially solves a nonlinear optimization problem online, producing an inverse control signal for the desired output at every time step, compensating the nonlinear effects of TSM. The results indicate that the presented model and control scheme are promising for motion control in any application utilizing TSM.