Soft continuum robots have broad application prospects due to their superior flexibility, compliance and safety. However, the high mechanical complexity addresses a major challenge in precise pose control modeling. Deep Deterministic Policy Gradient (DDPG) algorithm, as a foundational modelfree, off-policy method, is well-suited for such tasks. However, DDPG is known for its inherent instabilities, particularly its susceptibility to Q-value overestimation and challenges in sparse reward environments, which can hinder performance and efficiency. To address these limitations, this paper proposes a Hybrid Reward-Shaped DDPG and PSO fusion algorithm(HR-DP). This method integrates a multi-component reward function with the PSO algorithm, aiming to guide the agent's exploration more effectively and higher exploration accuracy. The target point tracking experiment by the two-segment soft continuum robot in simulation was performed. The results demonstrate that the robot controlled by HR-DP can achieve significantly faster convergence, higher cumulative rewards, higher accuracy and greater stability than that by the standard DDPG baseline and other state-of-theart methods. This work provides a practical and effective HR-DP algorithm enhanced from DDPG, which can benefit pose control of the multi-segment soft continuum robot in complex, real-world environment.

This paper investigates the dynamic characteristics of an H40 CNC machine tool worktable via operational modal analysis (OMA) to provide insights for enhancing the performance of high-speed, high-precision CNC machines. A modal testing scheme was established using 16 measurement points, and the modal parameters were identified from batch measurements using LMS TestLab software. The results were validated using the Modal Assurance Criterion (MAC), confirming the rationality of the analysis. This study provides a valuable reference for the dynamic analysis and optimization of similar machine tool components.

To address the flexible operation requirements of narrow workspace in minimally invasive surgery(MIS), this paper proposes a continuum robot system featuring cooperative traction-torsion actuation via flexible shafts. The flexible sections realize Omni-bendable movements by traction of the flexible shafts, while the rigid section achieves fine positioning through gear transmission driven by the rotary of the flexible shafts. In order to formulate the relation between the distal position of the continuum robot and the traction of the flexible shafts, a dynamics model is established in Adams to generate simulation data. A nonlinear mapping between the end-effector position and multi-flexible-shaft inputs is constructed by training the simulated data in a back-propagation(BP) neural network. O-shaped and Sshaped trajectory-tracking and pose-comparison tests are conducted in Adams-Matlab/Simulink co-simulation environment. The results demonstrates that the end effector of the continuum robot can achieve high positioning accuracy and stable tracking, validating the feasibility and potential application in MIS.

The confine workspace in minimally invasive surgery and the difficulty of installing force sensor at the distal of surgical instrument make it necessary for surgeons to rely on clinical experience to assess the safety of the surgical site. This paper proposes a force-sensor-free method for perceiving gripping force in the opening-and-closing mechanism of a surgical manipulator driven by a flexible shaft. By constructing a dataset between the rotational torque of the flexible shaft and the clamping force of the opening-and-closing mechanism, an end-toend mapping model between flexible shaft torque and clamping force is established by incorporating the dataset into a multi-layer perceptron(MLP) neural network model,. This enables the acquisition of the clamping force exerted by the surgical instrument on the target tissue without relying on pressure sensors at the instrument tip, thereby enhancing the immersion and safety of surgical procedures.

Performing a successful robotic grasping to uncertain objects in unstructured environments is challenging. This study presents a new compliant soft robotic gripper for objects handling and cap manipulation through the coordination of three soft fingers and in-hand manipulation. The experiments are conducted to validate that the soft robotic gripper can successfully realize simultaneous grasping and capping manipulations with only one flexible shaft actuation for every single soft finger.Note to Practitioners—Uncertain object manipulation tasks pose significant challenges to a robotic gripper while grasping and capping unknown objects without damaging them. The existing rigid grippers have experienced flexible manipulation through multiple degrees of freedom (DoFs) by complex mechanical structures, and the soft gripper can realize stiffness-compliant manipulation differently. The proposed novel robotic in-hand manipulation can execute grasping and cap manipulation by a single flexible shaft to simultaneously achieve bending and rotational movements. The relationship between stretching force and finger’s curvature can enable a custom design for user-specific applications.

This paper presents a visual feedback available robotic gait training system for motor recovery of hemiplegic stroke survivors. The system is composed of a treadmill consisting of two split belts, a pelvic support manipulator assisting patient's pelvic movement, and a visual interface feedbacking patient's gait phase. The split-belt treadmill allow patient to walk in different velocities between sound side and affected side legs, and detect patient's gait phase by current value of DC motor. The pelvic support manipulator provides three active actuations to assist patient's leg swinging during walk training. The virtual walking scenario gives visual feedback for patient while providing patient's gait phase calculated from motor current of the treadmill. One subject with simulated stroke participated in this study. Experiment results indicate gait phase of the virtual model can well track that of patient's walking, verify the feasibility of the proposed system to improve gait recovery during rehabilitation.

Eye-tracking technology has been applied to surgical skill improvement and can observe differences in gaze data between the experienced and novice surgeon. Some eye trackers can even detect pupil diameter. We hypothesized that differences in technical proficiency among surgeons affect the extent of changes in pupil diameter, because the higher mental workload a laparoscopic task requires, the larger the person's pupil diameter dilates. In this study, we recorded the pupil diameters of pediatric surgeons while they performed a suturing task in a dry box environment. The more proficient surgeons exhibited a smaller distribution in pupil diameter than did the less proficient surgeons. Our data indicate that an individual's suturing proficiency is closely related to the degree of dispersion of pupil diameter.

Minimally invasive surgery (MIS) is commonly used in pediatric operations. This method greatly benefits patients because of the reduced surgical trauma. To perform such surgery smoothly, doctors must be highly skilled. To reduce operating difficulties, a great deal of research on surgical systems have been carried out. However, in some cases, smaller workspaces limit the application of MIS. For example, the workspace of infant congenital esophageal atresia (ICEA) surgery is only around 30×30×30 mm. Until now, most ICEA surgeries have been manually performed with traditional instruments. This paper presents a smart surgical robot (SSR) for ICEA surgery. The robot is composed of two slave arms, each consisting of a positioning manipulator and a surgical tool manipulator. The positioning manipulator uses a selective compliance assembly robot arm (SCARA) and a screw-pair mechanism to achieve translational movement in 3D space, and the surgical tool manipulator uses a “double screw drive + universal joint” structure to allow an omni directional bending motion. During surgery, the surgeon first creates the workspace manually to explore the target esophagus. The SSR system is then applied to perform operation. The configuration of the SSR means it can perform tissue manipulation under endoscopic view in a small workspace. Experimental results show that the endoscopic view permits the SSR system to be operated intuitively and accurately in the target workspace.

Remote operation is commonly used in modern robotic assisted surgery. A surgeon sits beside the console to operate an input device to control the slave robotic instrument performing tissue manipulation, while guided by visual feedback. Most people have high more dexterity on one hand than in the other. Humans prefer to use their more dexterous hand to do important tasks, such as holding a needle for suturing, while the other hand is used to assist. However, surgeons need to perform important task using both hands on a surgery. For example, they sometimes need use left hand to hold scalpels or needles for vital tissue intervention even if they are right-handed. This paper presents a novel smart surgical robotic system for surgical application. The robotic system is composed of two slave arms and two visual modules. Each slave arm consists of a 8 degree of freedom dexterous manipulator. Each visual module is composed of a 3 DOF manipulator and a flexible endoscope. The two slave arms and the two vision modules are closely located in a rectangular frame. Two phantom Omnis are used for tele-control of the two slave arms for tissue manipulation. The correspondence between the phantom Omnis and the slave arms could be swapped depending on the surgical requirement. Therefore, the user could always use the most dexterous hand for vital tasks. The two visual modules, located in the front and the back of the two slave arms respectively are used for visual feedback. Based on the different correspondence between the master and the slave arms, only one visual module will be selected to show its image in a monitor. As a result, the operator could always drive the slave arms for tissue manipulation with good eye-hand coordination. The preliminary experiment shows that the surgical robotic system is adequate.

Recently, a large amount of stroke survivors are suffering from motor impairment. However, existed therapy interventions have limited effects to restore normal motor function. Thus, we proposed a novel control strategy for gait rehabilitation of hemiplegic patients. The whole system consists of a Functional Electrical Stimulation (FES) device and Treadmill-Walk system. FES contributes to improve the quality of the gait based on real-time adjustment of gait pattern. During gait, the electrical stimuli from separate output channels of an FES device are launched to stimulate two lower extremity muscles (Tibialis Anterior (TA) and Hamstrings). Stimulus launching procedure is based on identifying subject's gait state (stance and swing phases). According to the current variation of treadmill motor, gait phase and muscle activation of lower limbs can be determined during walking on Treadmill-Walk. Three able-bodied subjects simulated hemiplegic patients in the experiment. The results indicated that the proposed method is a safe, feasible and promising intervention.