Motion scaling is essential to empower users to conduct precise manipulation during teleoperation for robot-assisted microsurgery (RAMS). A constant, small motion scaling ratio can enhance the precision of teleoperation but hinder the operator from quickly reaching distant targets. The concept of self-adaptive motion scaling has been proposed in previous work. However, previous frameworks required extensive manual tuning of core parameters, which significantly depends on prior knowledge and may potentially lead to non-optimal solutions. This paper presents a hybrid offline reinforcement learning and damping control approach to regulate the motion scaling ratio for different operations during offline training. This method can take user-specific characteristics into consideration and help them achieve better teleoperation performance. Comparisons are made with and without using the adaptive motion-scaling algorithm. Detailed user studies indicate that a suitable motion-scaling ratio can be obtained and adjusted online. The overall performance of the operators in terms of time cost for task completion is significantly improved, while the variance of average speed and the total distance for robot operation is reduced.

Microsurgery involves the dexterous manipulation of delicate tissue or fragile structures, such as small blood vessels and nerves, under a microscope. To address the limitations of imprecise manipulation of human hands, robotic systems have been developed to assist surgeons in performing complex microsurgical tasks with greater precision and safety. However, the steep learning curve for robot-assisted microsurgery (RAMS) and the shortage of well-trained surgeons pose significant challenges to the widespread adoption of RAMS. Therefore, the development of a versatile training system for RAMS is necessary, which can bring tangible benefits to both surgeons and patients. In this paper, we present a Tactile Internet-Based Micromanipulation System (TIMS) based on a ROS-Django web-based architecture for microsurgical training. This system can provide tactile feedback to operators via a wearable tactile display (WTD), while real-time data is transmitted through the internet via a ROS-Django framework. In addition, TIMS integrates haptic guidance to ‘guide’ the trainees to follow a desired trajectory provided by expert surgeons. Learning from demonstration based on Gaussian Process Regression (GPR) was used to generate the desired trajectory. We conducted user studies to verify the effectiveness of our proposed TIMS, comparing users' performance with and without tactile feedback and/or haptic guidance. For more details of this project, please view our website: https://sites.google.com/view/viewtims/home.

In endoluminal surgery, the miniature instruments shall be of high accuracy and flexibility for minimal invasive diagnosis and surgical intervention. To this end, continuum robots with flexible joints have been proposed as the mechanism of endoscopic instruments. The compliance and deformability of the continuum joints enable access into the curved lumen. However, the manufacturing tolerances are normally not considered in the design procedure, and led to inaccuracy in the robotic control. To improve the control accuracy and flexibility of endoluminal surgical robots, we propose a novel design of a metal printed continuum joint in this paper, which incorporates a variable pitch design into the spring-like structure. The design can reduce the position errors accumulated on the distal tip of the joint, especially at large bending angles. The specification of variable pitch is investigated and determined with a friction model. In addition, to eliminate the distortion of the joint induced during the metal printing process, an extensive experiment was conducted to access the effect of the variables in the design (pitch, thickness, width and number of coils), with the aim of determining optimal parameters for reducing discrepancy caused by manufacturing variations. The final results indicated that the bending error of a single joint can be reduced from 18.10% to 4.63%, and a multi-segment prototype was developed to verify its effectiveness for potential surgical applications.

Gastrointestinal (GI) endoscopy is a conventional and prevalent procedure used to diagnose and treat diseases in the digestive tract. This procedure requires inserting an endoscope equipped with a camera and instruments inside a patient to the target of interest. To manoeuvre the endoscope, an endoscopist would rotate the knob at the handle to change the direction of the distal tip and apply the feeding force to advance the endoscope. However, due to the nature of the design, this often causes a looping problem during insertion making it difficult to be further advanced to the deeper section of the tract such as the transverse and ascending colon. To this end, in this paper, we propose a novel robotic endoscope which is covered by a rotating screw-like sheath and uses a spiral insertion technique to generate 'pull' forces at the distal tip of the endoscope to facilitate insertion. The whole shaft of the endoscope can be actively rotated, providing the crawling ability from the attached spiral sheath. With the redundant control on a spring-like continuum joint, the bending tip is capable of maintaining its orientation to assist endoscope navigation. To test its functions and feasibility to address the looping problem, three experiments were carried out. The first two experiments were to analyse the kinematic of the device and test the ability of the device to hold its distal tip at different orientation angles during spiral insertion. In the third experiment, we inserted the device in the bent colon phantom to evaluate the effectiveness of the proposed design against looping when advancing through a curved section of a colon. Results show the moving ability using spiral technique and verify its potential of clinical application.

This paper presents a versatile robotic system for sewing a 3D structured object. Leveraging on using a customized robotic sewing device and closed-loop visual servoing control, an all-in-one solution for sewing personalized stent graft is demonstrated. Stitch size planning and automated knot tying are proposed as two key functions of the system. By using effective stitch size planning, sub-millimetre sewing accuracy is achieved for stitch sizes ranging from 2mm to 5mm. In addition, a thread manipulator for thread management and tension control is also proposed to perform successive knot tying to secure each stitch. Detailed laboratory experiments have been performed to evaluate the proposed instruments and allied algorithms. The proposed framework can be generalised to a wide range of applications including 3D industrial sewing, as well as transferred to other clinical areas such as surgical suturing.