Qiqi Pan

Lateral force blind spots frequently trigger airway injuries during robotic bronchoscopy. Traditional sensing approaches lack fine spatial resolution, and single-segment robots suffer poor posture adjustment flexibility, worsening unmonitored tissue contact. We integrate a snake-scale-inspired 64-channel gradient piezoelectric film with a dual-segment manipulator to resolve lateral blind spots for secure bronchial navigation. The conformally wrapped sensor delivers fast ( 0.98, RMSE < 0.145 N, CV < 2%) and filters bending pseudo-forces. The dual-segment design enables coordinated proximal-distal motion to avoid overcontact in tortuous lumens. Phantom and ex vivo porcine lung tests confirm real-time force localization, 5.0 N safety alarms, and autonomous tuning to keep contact forces below 3.0 N. This synergistic robot-sensor design supplies a translatable safety control strategy for flexible surgical manipulators.

Robotic-assisted endovascular interventions have shown great potential to protect surgeons from prolonged X-ray exposure and improve the precision and outcomes of interventions. However, existing interventional robots remain limited in treating complex coronary lesions due to the lack of multi-instrument manipulation and high-precision force sensing and feedback. In this paper, a novel multi-instrument robotic system with integrated force sensing for complex endovascular interventions was developed and validated. The manipulation mechanism was designed to mimic surgeon’s fingers motions, achieving independently decoupled linear and rotational control to replicate natural manual operation. Additionally, a high-precision force sensing mechanism which is suitable for the multi-instrument delivery mechanism based on the lever amplification principle was proposed. This method can significantly reduce the length of the force transmission path and the impact of friction and inertial force, thereby enhancing the detection sensitivity of subtle vessel-tool interaction force during robot-assisted endovascular intervention. Furthermore, to address the issue of uncontrollable clamping force leading to instruments slippage and damage, a multi-roller adaptive clamping sensing mechanism based on series elastic actuation was designed and analyzed. Finally, several evaluation experiments were performed to validate that the precision and performance of the developed robotic system.

This study presents a two-segment continuum robot with piecewise stiffness, designed to enhance the precision, adaptability, and safety of tracheal intubation procedures. The robot employs a continuum manipulator (CM) as its end-effector, featuring a proximal segment (PS) with an aluminum alloy interlocking joint, which provides high axial stiffness for stable insertion, and a distal segment (DS) with a micro-nano resin-based notched structure, offering increased flexibility and compliance to navigate complex anatomical structures such as the epiglottis and vocal cords, thereby reducing airway trauma. To describe the motion behavior of the robot, a piecewise variable curvature kinematic model is developed, capturing the deformation characteristics of each segment under actuation. Furthermore, a piecewise stiffness analysis is conducted to determine the axial and bending stiffness of each segment, ensuring an appropriate balance between stability and flexibility. To enhance control precision, an active tendon-driven decoupling control strategy is introduced, effectively minimizing the interaction forces between flexible segments and improving end-effector maneuverability. The results demonstrate that the proposed design significantly improves the adaptability of the tracheal intubation robot, ensuring controlled insertion while reducing the risk of excessive force on the airway walls. This study provides theoretical and technical insights into the mechanical design and control strategies of continuum robots, contributing to the safety and efficiency of tracheal intubation.

The coupling effect of the flexible robotic arm with multiple degrees of freedom greatly increases the control complexity. For flexible endoscopic robots that manipulate an endoscope or other necessary channels like gas detection channel, its performance, like adaptability to tortuous paths, simplicity of control, and compactness of size are essential. Currently, there is a tradeoff between multiple-degree of freedom (DOF) and control accuracy of continuum robots. In this article, a self-decoupling continuum robot with multiple stiffness was proposed. Based on the difference in stiffness among segments, the proposed robotic arm can well realize the independent operation of each DOF. Using stiffness analysis and kinematics calculation, the optimal self-decoupling structure model of the robot was determined. With finite element analysis and experimental verification, the control error of the proposed robotic arm is less than 2.5%. The coupling error among segments is less than 6.7%, and the ratio of absolute maximum error to the length of the robotic arm is less than 1.4%.

Force sensing is important in robot-assisted minimally invasive surgery (MIS), but it is still difficult to achieve both miniaturization and multi-dimensional perception at the same time. A modular design scheme of a miniature six-dimensional force sensor that can be integrated into a MIS robot is proposed. The force and moment applied on the sensor are converted into the signal response of the pressure sensitive element, and the position of the pressure sensitive element is located by using flexible printed circuit board (FPCB), with which the wiring of signal circuits is simplified. The blind signal separation Fast Independent Component Analysis (FastICA) algorithm is used to decouple the output signal. The calibration experiment of the proposed sensor was carried out, and the calibration matrix was established. From the comparative experiment with commercial sensors, the accuracy, linearity, hysteresis, coupling error and other performance of the proposed sensor are verified. The maximum coupling error is 2.8% and the maximum stable measuring error is 3.9%. Analysis and experiments proved the rationality and scientificity of the sensor. This work opens up new ideas for the miniaturization, modularization and integration of sensors for surgical robots.