Ion wind technology holds potential for the miniaturization of flying microrobots, generating thrust without mechanical moving parts, enabling simplified and light designs free from high-frequency actuators. Nevertheless, two fundamental challenges have limited its practical implementation: insufficient payload capacity and inadequate controllability, particularly in multi-degrees-of-freedom flight. Here, we demonstrated an inertial measurement unit-based closed-loop controlled flight of a light (36.7 mg) ion-propelled microrobot, achieving a thrust-to-weight ratio of 5:1 and 1-h long-endurance tethered hovering without mechanical actuators. Experimental validation indicates that the control strategy enhances stability, with a decrease of 83.11% and 89.21% in the root mean square error of pitch and roll angle, respectively. Leveraging origami-inspired design and cost-effective metal-polymer composites, our manufacturing approach enables the rapid assembly of complex microrobots at a disposable cost, overcoming a key barrier to practical swarm deployment. The microrobot's high load capability allows it to carry a high-fidelity image sensor and a fiber Bragg grating sensor while maintaining sufficient maneuverability to complete predefined tasks such as environmental surveillance and material identification. This work introduces an approach to autonomous microrobotic swarm flight, suggesting potential applications in confined-space surveillance, disaster rescue, and hazardous environment exploration.

Retinal surgery demands submillimeter precision in constrained intraocular spaces, with subretinal injections requiring accurate bimanual coordination between surgical tools and illumination devices. This paper presents the Dual-Arm Robotic System for Subretinal Injection (DASSI), featuring a motion-decoupled Remote Center of Motion (RCM) mechanism and an initial placement strategy to optimize dual-arm workspace overlap. An Automatic Light Pipe Tracking algorithm with Guided Virtual Fixtures (ATLP-GVF) is developed to eliminate redundant light pipe motion when illumination needs are met. Integrated with its hardware design (motion-decoupled RCM mechanism) and ATLP-GVF, DASSI achieves precise performance: orientation tracking error (0.65 degrees +/- 0.28 degrees), depth error (1.86 mm +/- 0.93 mm), and stable illumination (tracking off-set ratio 26% +/- 14%). Notably, in the ex-vivo experiment, ATLP-GVF reduces light pipe movement duration to less than 10% of that with continuous tracking methods, representing a reduction of more than 90%. DASSI demonstrates potential to address bimanual coordination challenges in retinal microsurgery, offering a precise platform for complex procedures such as subretinal gene-therapy delivery.

Time-of-Flight Diffraction (TOFD) stands as the most accurate and widely adopted technique in nondestructive testing. Its efficacy heavily depends on precise measurement of the contact force between probe and test specimen. Conventional force sensing methods require intrusive adapter structures that impair measurement accuracy and preclude multi-point sensing. To overcome this limitation, this paper presents a novel Fiber Bragg Gratings (FBG)-integrated TOFD probe capable of in-situ force measurement. The proposed probe enables two-point force sensing and offers scalability toward multi-point measurement. A cross beam based FBG force sensor is proposed. Methods for range/accuracy determination are then developed based on the elastic deformation theory of fixed–fixed beam. Three sensor prototypes—with designed ranges/accuracies of 1 N/0.1 %, 10 N/1 %, and 10 N/2 % are fabricated and evaluated. Experimental results demonstrate calibrated accuracies of 0.09 %, 0.84 %, and 1.83 %, respectively. A 2.7 % average dynamic error across 1–10 Hz is also achieved. The p-values of measurement results range from 0.72 to 0.94 over a 1 h continuous test, indicating stable measurement performance. Finally, preliminary evaluation on a weld test block show that the probe simultaneously acquires TOFD images and in situ force, both contact force and probe orientation influencing imaging quality, and force measurements enable detection of probe misalignment.

In retinal surgery, membrane peeling is a challenging procedure that requires surgeons to limit peeling force and manage disturbance force at the millinewton level. This article presents a novel handheld compliant robot designed to assist in membrane peeling, featuring a five-chain parallel compliant module and a force-sensing tube. The compliant module is used to adjust the tip's transverse position actively, while the tube is designed to adsorb the membrane and sense the peeling force. The Jacobian matrix of the proposed robot is also derived. Then, a data process method based on wavelet decomposition and Kalman filtering is introduced to identify the disturbance force. A control method based on the Jacobian matrix is also proposed to compensate the disturbance force. Finally, the proposed robot is evaluated through bench test and handheld test, in which chicken chorioallantoic membrane is utilized as the ex-vitro model. The handheld test results show that the root mean square and maximum of disturbance force are reduced by 44.1% and 52.7%, respectively. The membrane detaches from the tube when the peeling force approaches 15 mN, which provides a passive safety guarantee of membrane peeling.

The handheld 3-Prismatic-Revolute-Spherical parallel compliant robot offers a viable solution for suppressing hand tremor and assisting membrane peeling via vibration. Achieving these tasks requires a thorough understanding of the robot’s dynamic behavior, including the coupled bending-torsion deformation of the spherical joint, the bending of the revolute joint, and the coupled behaviors of joints in parallel mechanisms. To address this challenge, this paper introduces a pseudo-rigid-body-based dynamic model for the proposed compliant robot and conducts optimization studies. First, a pseudo-rigid-body model with two orthogonally arranged elements and an additional torsional energy term is developed to capture the coupled bending-torsion behavior of the spherical joint. A pseudo-rigid-body model is also introduced to model the deformation of the revolute joint. Then, by combining the joint models and the robot’s configuration, a dynamic model of the proposed robot is established using the Lagrangian method. Using the proposed dynamic model, the relationships among the coupled bending-torsion deformation of the spherical joint, the bending of the revolute joint, and the motor’s driving force are analyzed under specified vibration frequencies and amplitudes. Next, the design parameters corresponding to the peak driving force, which reflects maximum stiffness, are determined through optimization. Finally, the dynamic model and optimization results are validated through experiments. Experimental results show that the dynamic model achieves approximately 7.58 μ m in both orthogonal and oblique directions at 15Hz, and a maximum driving force of 0.87N.

Robot-assisted membrane peeling provides several benefits including improvement of manipulation precision and safety. A forceps which is capable of sensing peeling force, scleral force, and insertion depth is the basis of developing robot control method. But such forceps still lacks. To relieve these challenges, a multi-function sensing forceps based on fiber bragg gratings (FBG) is proposed. Six FBG sensors are divided into three groups and attached along the grooves of a 23G forceps. The first FBG group aims to measure the peeling force, while the other two FBG groups measure the scleral force and insertion depth. The calculation algorithm is built. Both linear calibration method and radial basis function (RBF) neural network calibration method are proposed to improve the sensing accuracy. Experimental results show that the precision of the RBF neural network is approximately 76.28% higher than that of linear calibration method. Verification experiments results show that the average root mean square error of the proposed forceps are 0.28 mN (peeling force), 0.37 mN (scleral force), and 0.29 mm (insertion depth), respectively. The tested sensing range are 30 mN (peeling force), 100 mN (scleral force), 10 mm (insertion depth), respectively.

Hybrid compliant mechanism (HCM), a kind of ophthalmic robot, offers a potential way to suppress the fluctuation force in continuous curvilinear capsulorhexis. The fluctuation force is caused by the involuntary interaction between forceps and the grasped membrane. The HCM is expected to control the fluctuation force for all types of grasped membrane, regardless of their lengths (1–7 mm), widths (1–3 mm), Young’s modules (2–3.4 MPa), and driving frequencies (8–12 Hz). This paper aims to optimize the HCM’s performance while taking the dynamic response of the grasped membrane into account. A five-chain HCM with force-sensing forceps is proposed, along with a pseudo-rigid body model. Then, the dynamic interaction model between HCM and membrane loaded is developed. Next, analyze the effect of HCM and membrane parameters on the interaction force, and optimize the HCM. The optimization results are verified through experiments, in which polydimethylsiloxane (PDMS) is used as membrane-loaded. In experiments, the maximum interaction force is 4.26 mN (x, 10 Hz)/3.73 mN (y, 10 Hz) when the length, Young’s module, and width of the membrane are 8 mm, 2 MPa, and 1 mm, respectively.

Retinal vein cannulation involves puncturing an occluded vessel on the micron scale. Even single millinewton force can cause permanent damage. An ophthalmic robot with a piezo-driven injector is precise enough to perform this delicate procedure, but the uncertain viscoelastic characteristics of the vessel make it difficult to achieve the desired contact force without harming the retina. The paper utilizes a viscoelastic contact model to explain the mechanical characteristics of retinal blood vessels to address this issue. The uncertainty in the viscoelastic properties is considered an internal disturbance of the contact model, and an active disturbance rejection controller is then proposed to precisely control the contact force. The experimental results show that this method can precisely adjust the contact force at the millinewton level even when the viscoelastic parameters vary significantly (up to 403.8%). The root mean square (RMS) and maximum value of steady-state error are 0.32 mN and 0.41 mN. The response time is below 2.51 s with no obvious overshoot.

This study proposed the use of the minimum slip force as an indicator to measure the clamping ability of microsurgical forceps. By analyzing the minimum slip forces of four typical tooth types of microsurgical forceps, the clamping capacity of each type was evaluated. Among the existing tooth forms, the staggered tooth type exhibited a relatively large minimum slip force. Consequently, a new tooth-shaped structure for microsurgical forceps - the hemispherical convex structure was proposed. Simulation and experimental studies demonstrated that this new dental structure could achieve stable and reliable clamping.

视网膜下注射人胚胎干细胞是治疗视网膜变性的一种有效术式,该术式对医生手术操作的精准性、稳定维持能力、安全性均提出了很高的要求.为此,提出一种基于主从式机器人的视网膜下注射系统,辅助医生完成视网膜下注射操作.构建从手机器人的正逆运动学模型,然后进行视网膜下注射手术运动分析,确定从手机器人的运动要求.建立主手和从手机器人之间的运动映射关系,依据运动映射关系推导建立远程运动中心(RCM)点位置调整运动、术中RCM运动的状态切换和分离过程的速度映射模型.通过离体猪眼球视网膜下穿刺注射实验对机器人的精确性和稳定维持能力进行验证,结果表明:机器人辅助操作系统末端注射针具有稳定维持能力和运动的精确性,机器人辅助操作比徒手操作对视网膜造成的创伤更小,注射更稳定.

Purpose Robot assistance in membrane peeling may improve precision and dexterity or prevent complications by task automation. To design robotic devices, surgical instruments’ velocity, acceptable position/pose error, and load ability need to be precisely quantified. Methods A fiber Bragg grating and inertial sensors are attached to forceps. Data collected from forceps and microscope images are used to quantify a surgeon's hand motion (tremor, velocity, posture perturbation) and operation force (voluntary and involuntary) in inner limiting membrane peeling. All peeling attempts are performed on rabbit eyes in vivo by expert surgeons. Results The root mean square (RMS) of the tremor amplitude is 20.14 µm (transverse, X), 23.99 µm (transverse, Y), and 11.68 µm (axial, Z). The RMS posture perturbation is 0.43° (around X), 0.74° (around Y), and 0.46° (around Z). The RMS angular velocities are 1.74°/s (around X), 1.66°/s (around Y), and 1.46°/s (around Z), whereas the RMS velocities are 1.05 mm/s (transverse) and 1.44 mm/s (axial). The RMS force is 7.39 mN (voluntary force), 7.41 mN (operation force), and 0.5 mN (involuntary force). Conclusions Hand motion and operation force are measured in membrane peeling. These parameters provide a potential baseline for determining a surgical robot's accuracy, velocity, and load capacity. Translational Relevance Baseline data are obtained that can be used to guide ophthalmic robot design/evaluation.

An epiretinal membrane (ERM) is a fibrocellular proliferation on the inner surface of the retina causing blurred and distorted central vision. Surgery is the only effective method for ERM removal. This paper investigated the mechanical properties of ERM peeling using the finite element (FE) method. A FE model of ERM formation on the retina surface was constructed. The failure criterion was applied to the attachment pegs to represent the adhesive force between the ERM and retina. The simulation results were consistent with the experimental data in published research. The maximum peeling force was 4.1 mN at a peeling velocity of 2 mm/s and an angle of 30°. The peeling force was minimum at the peeling angle of 45° and increased with the increase in peeling velocity and Young's modulus of the membrane. The outcome of this paper can improve the safety and efficiency of ERM removal.

Purpose Continuous curvilinear capsulorhexis (CCC), as a prerequisite for successful cataract surgery, is one of the most important and difficult steps in phacoemulsification. In clinical practice, the size and circularity of the capsular tear and eccentricity with the lens are often employed as indicators to evaluate the effect of CCC. Methods We present a neural network-based model to improve the efficiency and accuracy of evaluation for capsulorhexis results. The capsulorhexis results evaluation model consists of the detection network based on U-Net and the nonlinear fitter built from fully connected layers. The detection network is responsible for detecting the positions of the round capsular tear and lens margin, and the nonlinear fitter is utilized to fit the outputs of the detection network and to compute the capsulorhexis results evaluation indicators. We evaluate the proposed model on an artificial eye phantom and compare its performance with the medical evaluation method. Results The experimental results show that the average detection error of the proposed evaluation model is within 0.04 mm. Compared with the medical method (the average detection error is 0.28 mm), the detection accuracy of the proposed evaluation model is more accurate and stable. Conclusion We propose a neural network-based capsulorhexis results evaluation model to improve the accuracy of evaluation for capsulorhexis results. The results of the evaluation experiments show that the proposed results evaluation model evaluates of the effect of capsulorhexis better than the medical evaluation method.

Continuous curvilinear capsulorhexis (CCC) requires surgeons to manipulate fragile eye tissue at the microscale. The limited perceptual accuracy of surgeons makes it difficult to precisely position the forceps. Robot technology provides a feasible way to improve the performance of CCC.

Continuous curvilinear capsulorhexis (CCC) is a delicate ophthalmic procedure which may benefit from robot technology. Measuring the behaviours (physiological tremor, operation force) of surgeons provides baseline data to develop assistive CCC robot.

Controlling the operation force in membrane peeling is a challenging task in ophthalmic surgery. Hybrid compliant mechanism (HCM) provides a feasible method to address this problem. In this method, operation force is controlled by stretching the clamped trapezoidal membrane. The operation force is related to the dynamic characteristics of the HCM and trapezoidal membrane. This study aims to build a dynamic interaction model that describes the dynamic process of HCM stretching trapezoidal membrane. An HCM with a force-sensing tip is proposed, and the pseudo-rigid-body model of the proposed HCM is given. The trapezoidal membrane is regarded as a variable cross-section linear elastic element. Then, the dynamic model of HCM and trapezoidal membrane are developed using the Lagrange equation. The constraint relationship between HCM and trapezoidal membrane is derived, and the dynamic interaction model is developed. Finally, the dynamic interaction model is verified by stretching six polydimethylsiloxanes (PDMS) samples and two human anterior lens capsule (ALC) samples with the proposed HCM. Experimental results show the average relative errors of the dynamic interaction model are 10.78% (PDMS) and 8.79% (human ALC), respectively.

：To realize RCM (remote center of motion) motion mode required for robot-assisted intraocular surgeries, a novel six-degree-of-freedom series-parallel hybrid mechanism (RP+PPRRP/PPRR) is proposed.Firstly, inspired by the structure of U pair (Universal pair), the parallel configuration (PPRRP/PPRR) is reconstructed by two sets of planar five-bar mechanism (RPPRP) units.After calculating the DOFs (degrees of freedom) and analyzing their characteristics based on screw theory, the capability of RCM motion mode for this mechanism is confirmed.Subsequently, the forward kinematics model and the inverse kinematics model of this mechanism containing RCM parameters are established through coordinate transformation method.Then, according to the configuration of the mechanism, a physical prototype is designed and established.Finally, based on master-slave control method, a motion experiment is performed to verify the correctness of the kinematic model and the adaptability of this mechanism to intraocular surgeries.

为解决传统的基于三点法的质心测量系统无法应用于带翼展飞行器的问题,提出了一种基于三点方式的任意旋转角质心测量法.为了提高系统测量精度,采用响应面法分析多种随机误差对系统测量精度的综合影响.首先,构建了带翼展飞行器的质量质心测量系统,然后利用随机误差传递公式得到各个随机误差与系统测量精度之间的关系式,并使用响应面法和拉丁超立方抽样法得到多种随机误差与系统测量精度之间的二次项关系式模型,进而依据二次项关系式模型和系统精度指标得到各元器件的精度要求,并分析了满足系统测量误差的旋转角度范围.最后对200 kg、400 kg、800 kg三种质量级别的待测带翼展飞行器在不同旋转角度下进行了多次测量,并将响应面计算结果与理论值进行了对比.对比结果表明,质心测量精度满足系统精度要求,从而验证了任意旋转角度下该测量方法的有效性,以及随机误差与系统测量精度之间的二次项关系式模型的正确性.

Continuous curvilinear capsulorhexis (CCC) is a delicate ophthalmic procedure that may benefit from robot technology. In CCC, surgeons make an incision in the cornea, insert forceps into the anterior segment through the incision, and peel the anterior lens capsule (ALC) from the lens. The absence of perception of axial peeling force applied to ALC is challenging in developing robot-assisted CCC. A potential way to deal with this challenge is measuring axial force with a mercantile force sensor, which has the advantage of sub-millinewton precision, high axial stiffness, high stability, and ease of use. However, the measured results of the mercantile force sensor contain the axial peeling force and forceps-cornea friction. Therefore, we seek to estimate the friction at the incision with the distributed LuGre friction model. The normal force and friction at incision are measured by fiber bragg grating (FBG) sensors and a mercantile force sensor, respectively. Then, the parameters of the LuGre model are identified by applying a low-frequency sinusoidal movement on the forceps. An identification experiment is performed on ex-vivo pig cornea samples. Finally, friction during inserting forceps into the anterior segment of ex-vivo pig eyes is estimated. The root mean square error of friction identification and estimation are 0.59 mN and 1.59 mN, respectively.

Capsulotomy in cataract surgery is delicate and susceptible to surgeon fatigue, limited perception accuracy, and physiological hand tremors. To aid cataract surgery, we propose a novel vision-guided hybrid robot system. The robot, consisting of a PPRR/PPRRP parallel unit and an RP serial unit (R: rotation pair, P: prismatic pair), adopts a parallel configuration as the base. Capsulotomy has high requirements for position accuracy, thus, a robot control algorithm with the RCM constraint is proposed. This algorithm reduces the position error of the robot by limiting the position error within tolerance, thereby increasing the motion accuracy and smoothing the trajectory. Instead of obtaining position information based on the visual perception of the surgeons, we propose an edge detection method based on the U-Net to provide visual feedback to the robot.Experimental validations on a standard circle and ex-vivo pig eyeballs are performed to verify the effectiveness of the proposed robot control algorithm with the RCM constraint and the accuracy of the proposed robot system. When a circular trajectory of 5 mm is tracked, the maximum position error of the actuator end point is 0.084 mm and that of the RCM point is 0.292 mm. When the edge of the anterior capsule is tracked, the mean tracking error of the robot is 0.129 mm and that of the doctor is 0.764 mm.