For objects with complex topological and geometrical features, stochastic topological grasping can be executed without the necessity for feedback or precise planning. However, this grasping method has two significant limitations. First, the technique's effectiveness is reduced when interacting with topologically and geometrically simple objects like spheres, cubes, and cylinders, due to the inherent variability in grasping patterns. Additionally, the method's low stiffness restricts its ability to securely handling heavier objects. To address these challenges, this paper proposes an entanglement soft robotic gripper with variable stiffness and two transformed grasping modes (entanglement and clamping modes). The gripper contains three filaments, which can enhance the stiffness through the mechanism of layer jamming. Furthermore, the entanglement mode and the clamping mode, can be transformed by adjusting the working length of the filaments. The grasping performance comparison with and without variable stiffness was carried out, and the results indicated that the implementation of variable stiffness led to a 149 % increase in payload weight. Through experimental validation, we successfully employed the gripper in variable stiffness and transformed modes to grasp items with various shapes and weights. Demonstration of grasping heavier objects and transforming between two grasping modes were also conducted to showcase the adaptability and versatility of the gripper.

Ensuring both mobility and stability during colonoscopy is crucial for enhancing procedural efficiency and reducing the risk of complications. Traditional colonoscopy robots face challenges due to the fixed diameter of the colonoscope and the variability in colon anatomy. To address this, we propose a soft automatic anchoring system (SAAS) to enhance mobility and stability in colonoscopy robots. The SAAS features proximal and distal soft balloon anchors, employing origami principles to achieve a 42.2% higher maximum expansion capability compared to conventional flat surface anchors. With real-time pressure feedback, the SAAS automatically anchors upon contact detection, ensuring precise anchoring without overinflation while adapting to colon diameter variations and robot posture changes. Experimental results show a tenfold reduction in displacement during the stability test, significantly enhancing the robot’s performance under external loads. Performance comparison tests in phantom further demonstrated notable improvements in the efficiency of colonoscopy procedures using the SAAS. This system has the potential to greatly enhance the safety, precision, and overall efficiency of colonoscopy, offering substantial benefits for both medical practitioners and patient outcomes.

As one of the effective closed-loop control methods, visual servoing control methods are widely applied to continuum robots. However, existing visual servoing control methods mostly focus on accurate control of the robot’s end-effector, with less consideration given to the robot’s shape. In this work, a spatial position-based visual servoing obstacle-avoidable shape control framework for an 11-degree-of-freedom (DOF) hybrid continuum robot is proposed. In the control framework, a set of markers representing the shape of the continuum robot are measured and two spatial arcs are used to fit the shape. When controlling the redundant DOFs of the robot, position-based visual servoing shape control combined with obstacle avoidance is formulated as a quadratic programming problem, yielding the optimal solution at each sample time for the joint velocity vector of the 11-DOF hybrid continuum robot. Several experiments are conducted to validate the proposed control framework, which indicates the accuracy of the shape control achieves 0.88 mm.

Flexible endoscopes are commonly adopted in narrow and confined anatomical cavities due to their higher reachability and dexterity. However, prolonged and unintuitive manipulation of these endoscopes leads to an increased workload on surgeons and risks of collision. To address these challenges, this paper proposes a CT-guided control framework for the diagnosis of maxillary sinusitis by using a robotic flexible endoscope. In the CT-guided control framework, a feasible path to the target position in the maxillary sinus cavity for the robotic flexible endoscope is designed. Besides, an optimal control scheme is proposed to autonomously control the robotic flexible endoscope to follow the feasible path. This greatly improves the efficiency and reduces the workload for surgeons. Several experiments were conducted based on a widely utilized sinus phantom, and the results showed that the robotic flexible endoscope can accurately and autonomously follow the feasible path and reach the target position in the maxillary sinus cavity. The results also verified the feasibility of the CT-guided control framework, which contributes an effective approach to early diagnosis of sinusitis in the future.

Remote center of motion (RCM) has become a rising research direction in the field of robotics. It means that a robot with a rod-shaped end-effector operates through a tiny hole on the surface. Thereinto, a key issue is the deviation of the RCM point's position, apart from the operating accuracy. In addition, considering that an RCM robotic system generally consists of a commercial robot and a specialized rod-shaped end-effector, there exist some errors in the structural information related to the attached end-effector. In this article, a remote center of cyclic motion scheme with a data-driven technology is proposed to control robots, of which end-effectors' structural parameters are inaccurate. Meanwhile, a recurrent neural network is proposed to figure out the scheme's solution, with the relevant theoretical analysis given. Furthermore, simulative and physical experiments on a FRANKA Panda robot with a rod-shaped end-effector are conducted to validate the control scheme's effectiveness distinctly.

This study focuses on an adaptive fault-tolerant boundary control (BC) for a flexible string (FS) in the presence of unknown external disturbances, dead zone, and actuator fault. To tackle these issues, by employing some transformations, a part of the unknown dead zone and external disturbance can be regarded as a composite disturbance. Subsequently, an adaptive fault-tolerant BC is developed by utilizing strict formula derivations to compensate for unknown composite disturbance, dead zone, and actuator fault in the FS system. Under the proposed control strategy, the closed-loop system proves to be uniformly ultimately bounded, and the vibration amplitude is guaranteed to converge ultimately to a small compact set by choosing suitable design parameters. Finally, a numerical simulation is performed to demonstrate the control performance of the proposed scheme.