Recently, flexible robotic systems are developed to enhance minimally invasive interventions on internal organs located in confined areas of human body. These surgical devices are designed to navigate anatomical pathways via single-port access, such as natural orifices or minimal incisions and intraluminal interventions. With improved precision, spatial flexibility and dexterity, the robotic technology can enhance surgery such that minimally invasive flexible access would become a faster, safer, and more convenient method for intra-body interventions without multiple or wide incisions. However, a lot of works are still required for global acceptance of existing flexible robotic surgical platforms. This review provides extended insights on the design details of two types of flexible robotic systems used for endoscopic and endovascular procedures. As of today, several prototypes of both platforms have been proposed; however, their global acceptability and applicability remains very low. To address these, we present an extensive review on design constraints and control methods which are vital for safer, faster, and better operation of the flexible robotic systems in minimally invasive surgery (MIS). Finally, research trends of flexible robotic systems and their clinical application status in MIS are discussed along with some of the technical and technological challenges hindering their prominence.

Soft robotic hand/gloves for hand rehabilitation can aid the performance of activities of daily living (ADL). Although existing soft robotic hands can assist with finger flexion, few have addressed finger extension, which is a challenging task for stroke patients due to poststroke spasticity. In this article, we describe the design of a composite actuator, the soft-elastic composite actuator (SECA), to facilitate both finger flexion and extension. A double-segmented SECA comprising two serially connected fiber-reinforced actuators with two bottom torque-compensating layers was fabricated. The SECA bends and extends by pneumatic actuation, and the torque-compensating layers offer an assistive bending moment to configure the bending moment inside the SECA. The principles associated with selection of the torque-compensating layer are described. Analytical models were established to quantify the input pressure and the bending angle of SECA with free bending and when placed on a model compromised hand. The analytical models were validated experimentally and by the finite element method. Moreover, a stroke survivor was recruited to test the new robotic glove integrated with the multiple double-segmented SECA. The robotic glove facilitated hand opening and closing by the patient, and successfully assisted with grasp of a Chinese chess piece and twisting of a towel.

Automation in robotic surgery has become an increasingly attractive topic. Though full automation remains fictional, task autonomy and conditional autonomy are highly achievable. Apart from the performance of task fulfillment, one major concern in robotic surgery is safety. In this paper, we present a flexible endoscope that can help to guide the minimally invasive surgical operations automatically. It is developed based on the tendon-driven continuum mechanism and is integrated with the da Vinci Research Kit (DVRK). In total, the proposed flexible endoscope has six degree-of-freedoms (DOFs). Visual servoing is adopted to automatically track the surgical instruments. During the tracking, optimal control method is used to minimize the motion and space occupation of the flexible endoscope, which will improve the safety of both the robot system and the assistants nearby. Comparing with the existing rigid endoscope, both the experimental results and the user study results show that the proposed flexible endoscope has advantages of being safer and less space occupation without reducing its comfort level.

This article designs and analyzes a recurrent neural network (RNN) for the visual servoing of a flexible surgical endoscope. The flexible surgical endoscope is based on a commercially available UR5 robot with a flexible endoscope attached as an end-effector. Most of the existing visual servo control frameworks of the robotic endoscopes or robot arms have not considered either the physical limits of the robot or the remote center of motion (RCM) constraints (i.e., the fulcrum effect). To tackle this issue, this article first conducts the kinematic modeling of the flexible robotic endoscope to achieve automation by visual servo control. The kinematic modeling results in a quadratic programming (QP) framework with physical limits and RCM constraints involved, making the UR5 robot applicable to surgical field. To solve the QP problem and accomplish the visual task, an RNN activated by a sign-bi-power activation function (AF) is proposed. The motivation of using the sign-bi-power AF is to enable the RNN to exhibit an accelerated finite-time convergence, which is more preferred in time-critical applications. Theoretically, the finite-time convergence of the RNN is rigorously proved using the Lyapunov theory. Compared with the previous AFs applied to the RNN, theoretical analysis shows that the RNN activated by the sign-bi-power AF delivers an accelerated convergence speed. Comparative validations are performed, showing that the proposed finite-time convergent neural network is effective to achieve visual servoing of the flexible endoscope with physical limits and RCM constraints handled simultaneously.

This paper presents an experimental study on how different body flapping patterns affect the performances of fish cruising. First, a biomimetic robot fish is designed and built as the experimental platform, which mimics the skeleton structure and the muscle arrangement of real fish. Moreover, an improved Central Pattern Generator (CPG) is developed to generate different patterns, which are characterized by four control parameters: (1) the amplitude, (2) the frequency, (3) the time ratio between the beating phase and half cycle, (4) the shape parameter. Then, a number of experiments are conducted to investigate the thrust, the recoil, the cruising speed and the swimming efficiency. Based on the experimental results, following conclusions can be drawn: (1) Fish cruising follows the traveling wave model proposed in Lighthill's Elongated Body Theory. This model offers a balance between the thrust generation and the recoil, which results in a good swimming speed and high efficiency. (2) The time asymmetry of the body flapping patterns reduces the thrust. (3) The triangular pattern offers the smallest recoil and the cambering sinusoidal pattern gives the largest thrust. These findings provide better understandings on how fish swims and can be used as guidelines for designing the body flapping patterns for robot fish.