Thin-walled aircraft components are highly prone to deformation during positioning, which can lead to forced assembly and stress concentration. Once the structure is removed from the tooling, stress release may cause significant shape distortion. Conventional positioning layout design relies heavily on deformation simulations, which are often limited in accuracy, efficiency, and applicability. To address these challenges, this study introduces a stiffness distribution guided positioning layout design method. Specifically, the concept of a stiffness field along the minimum-stiffness direction is proposed, and a positioning layout feature map is used to construct paired image datasets. A conditional generative adversarial network featuring a multi-scale generator, an enhanced convolutional block attention module, and a multi-scale discriminator is developed to enable rapid prediction of stiffness fields from given positioning layouts. Moreover, three stiffness-distribution evaluation indices are defined based on the predicted stiffness field. Together with the pre-trained deep learning model, these indices form a solver integrated into NSGA-III, with additional engineering constraints incorporated. Finally, a case study on the rear fuselage of a fighter aircraft demonstrates the implementation of the proposed stiffness-field prediction and positioning layout algorithms. A flexible tooling system with reconfigurable positioning points is designed for experimental validation. Results show that the proposed method limits deformation in the minimum-stiffness direction to 0.790 mm. Compared with the baseline positioning layout, average deformation is reduced by 20.3 %, stress distribution becomes more uniform, and both maximum and average stress decrease by 24.8 % and a noticeable margin, respectively.

In advanced manufacturing fields such as aerospace, achieving high-precision cooperative positioning for dual-robot systems remains a critical challenge. Conventional calibration methods usually treat geometric error sources separately and calibrate them step by step, which can cause residual errors from one stage to propagate into the next and makes it difficult to compensate coupled system errors. This paper proposes a unified calibration framework to address this limitation. The master robot, the slave robot, and the base-to-base relationship are modeled as a single continuous kinematic chain. Based on this unified model, a cooperative error Jacobian matrix is derived for 78 geometric error parameters, and the Levenberg–Marquardt algorithm is used for parameter identification. Experimental results show that the mean absolute positioning errors in the x, y, and z directions decreased from 1.386 mm, 1.361 mm, and 0.341 mm to 0.391 mm, 0.387 mm, and 0.245 mm, corresponding to reductions of 71.8

This paper proposes a dynamics modeling method for industrial robots based on multibody systems transfer matrix method, aiming to overcome the computational complexity limitations of traditional dynamics modeling approaches in multi-degree-of-freedom systems. By decomposing the robot into modular subsystems (joints and links), the transfer matrices and equations that accurately characterize module’s mechanical properties are established. The system’s overall transfer equation is derived through sequential connection of component transfer matrices. The proposed method has the advantages of not requiring the global dynamics equations, high programmability and low system matrix order. A dynamics test platform for industrial robots is developed. First, the friction torque of each joint is identified using measured joint torque data. Subsequently, the dynamics model is combined to obtain the motion trajectory of the robot joint angle changes and joint angular velocity, and then verifies the simulation accuracy of the model.

The deformation and stress have vital influences on the geometric accuracy and mechanical property of assembly structure that determine the quality of aircraft product. In order to realize real-time perceptions and controls of deformation and stress in aircraft assembly, a hybrid modelling strategy is proposed to determine the static response of the assembly structure composed of parts with high and low rigidities. The parts are meshed and separately applied by linear and nonlinear analysis models to represent explicit mappings from nodal force to nodal displacement and stress. The linear model of high-rigid part with invariant stiffness is established by the method of influence coefficient, while the nonlinear static response of low-rigid part with variable stiffness is represented by the Kriging model that is trained by the dataset of displacement and stress under multiple groups of loads. Combining individual model of each part by the application of coupled degree of displacement freedom to the nodes on connection surface, a hybrid analysis model of the whole assembly structure is established. Attributed to the decoupling of linear and nonlinear terms in the Kriging model, all the parameters in the hybrid model can be identified offline, and the mappings from force to displacement and stress of the assembly structure are rapid for real-time computation. The indicators evaluating the stress concentration and displacement magnitude are established, and a multi-objective optimization model of holding forces is further established and solved for the regulations of deformation and stress on the assembly structure. A software and a flexible fixture with servo system are developed to monitor and control the assembly stress and deformation. Simulation results show that the hybrid model can represent the static response of the assembly structure precisely and the optimization of holding force can suppress the stress and deformation efficiently. The maximum analysis errors of total displacement and Von-Mises stress on the assembly structure are separately 0.032 mm and 8.2 MPa corresponding to their real data of 0.45 mm and 186 MPa, while the displacement and stress are controlled below 0.009 mm and 1 MPa after the optimization of holding force. Experimental verification demonstrates that the assembly deformation and stress can be instantly perceived and regulated online by the sensing and controlling of holding forces.

In this study, two types of rivets, solid and blind rivets, are employed to repair delaminated composite components with varying curvatures. The forced assembly behavior of these riveted joints under drilling depth deviations and angular misalignments is systematically investigated through a combination of finite element analysis and experimental testing. The initiation and evolution of damage within the composite joints are also characterized. A three-dimensional elastoplastic damage constitutive model is developed, accounting for anisotropic material behavior, nonlinear response, and progressive damage. Based on this model, plastic deformation, multiphase damage, and residual stresses in the riveted composite joints are predicted and validated experimentally. The results demonstrate that the numerical model accurately captures the forced assembly process and microscale damage evolution around the rivet hole. In solid-riveted joints, plastic deformation propagates in a V-shaped pattern along the rivet axis, whereas in blind-riveted joints, it forms a “pine tree” distribution around the hole. The drilling depth deviation enhances the axial constraint stiffness of the rivet fasteners but also exacerbates localized damage in the countersink region. Angular misalignment produces asymmetric stress distribution across the joint, promoting unidirectional delamination propagation.

The inherently low dynamic stiffness of industrial robots presents a fundamental obstacle to their full potential in high-precision milling applications, such as those in the aerospace sector. The resulting vibrations severely compromise machining quality and limit production efficiency. To address this problem, a high-bandwidth piezoelectric active damping toolholder is developed as a local micro-actuation unit for robotic milling. Distinct from conventional end-effector designs, the proposed toolholder adopts a local dynamic design strategy to reduce interference between the toolholder dynamics and the pose-dependent structural modes of the robot. Furthermore, a model-independent multi-harmonic adaptive feedforward control strategy is introduced to suppress spindle-related vibration harmonics without requiring real-time identification of the robot system. To evaluate the effectiveness and robustness of the proposed approach, milling experiments were conducted on two distinct industrial robot platforms under multiple validation scenarios. Initial validation on an ESTUN ER220 robot, machining a 5A06 aluminum alloy aerospace panel prototype, demonstrates maximum reductions in the root-mean-square values of vibration acceleration at the toolholder in the X, Y, and Z directions of 45.10%, 49.74%, and 50.61%, respectively, together with a surface roughness Sa reduction of up to 64.1%. Subsequent experiments on a KUKA KR500 heavy-duty robot further confirmed the effectiveness of the proposed toolholder under representative, posture-varying, chatter-prone, and variable-condition milling scenarios. The results support the robustness and cross-platform applicability of the proposed local active damping approach for improving vibration behavior and surface quality in robotic milling.

Accurate center recognition of aircraft skin seams is critical for ensuring the sealing quality and operational safety of sealing cobot systems. However, existing methods exhibit limited accuracy and robustness due to challenges such as local deformation, incomplete data, and structural defects. To address these issues, a robust and precise center recognition method is proposed utilizing profile data acquired by a line laser profilometer. A boundary point extraction method is developed by integrating local geometric and statistical features. Sidewall and bottom data are removed using the local directional magnitude ratio (LDMR) and density clustering (DC) methods, respectively. Subsequently, a local vector feature (LVF) is designed to extract the boundary points of the skin seam. To further enhance robustness, an anomalous center point detection and correction strategy based on the robust smoothing spline (RSS) is introduced. By introducing adaptive weighting and curvature smoothing terms, accurate curve fitting is achieved. The method is validated using profile data of aircraft skin seams with various morphological characteristics. Experimental results demonstrate that the average center recognition error is only 0.05 mm, and there are significant improvements in accuracy and robustness compared to existing methods. The method satisfies the path accuracy requirements for sealing operations performed by cobots on aircraft skin seams.

Carbon fiber reinforced polymer (CFRP) structures require efficient and reliable repair after sustaining local damage. This paper proposes an electrothermal co-curing bonding stepped repair method for CFRP by embedding a carbon nanotube film (CNTF) into the adhesive layer, endowing the repair with both Joule heating and self-sensing functionalities. The electrothermal and sensing properties of the CNTF are first discussed, followed by analyses of curing monitoring and forming quality, mechanical performance and damage sensing. The influence mechanism of the curing cycle on repair performance is then clarified. Results show that the CNTF exhibits not only rapid, stable, and uniform electrothermal performance but also a sensitive electrical resistance response to strain. Compared with conventional repair, electrothermal repair shows superior performance in temperature control and energy consumption, and both methods produce no obvious defects in forming quality. The resistance signal of the embedded CNTF can be used both to infer the cure evolution of the resin during the co-curing process and to detect damage initiation and propagation in the repaired structure under three-point bending loads. The embedding of the CNTF alters the local failure behavior of the stepped repair structure and slightly weakens its bending performance, though the effect is not significant. Furthermore, extending the holding time optimizes the distribution of curing-induced residual stress (CRS). When the holding time increases from 90 min to 150 min, the ultimate load recovery ratio rises from 75.89% to 83.34%, albeit with a diminishing beneficial effect. This study demonstrates that the CNTF holds promise as an integrated heating and sensing unit for in situ curing repair and condition monitoring of CFRP structures.

Countersunk holes are widely used to achieve flush riveting in aircraft panels, while the geometric deviations introduced during machining can compromise the assembly quality of riveted joints. In this study, the forced-assembly behavior of composite countersunk riveted joints under various countersunk-hole geometric deviations is investigated. A three-dimensional elastoplastic progressive damage model is developed to predict the plastic deformation, residual stress distribution, and multiple damage modes in composite joints. The assembly deformation and damage evolution of flat- and curved-plate joints are comparatively investigated using experiments and numerical simulations. The results show that the countersink-depth deviation intensifies the nonuniform expansion of the rivet and consequently requires a higher riveting force than the ideal joint. The increased interference shifts the peak hoop tensile stress away from the hole edge and aggravates assembly damage within the composite laminate. For joints with hole-axis angle deviations, posture adjustments of the rivet during forming produce asymmetric radial clearances on the two sides of the hole, resulting in nonuniform hole expansion and residual hoop stress. The plastic strain field and damage zone propagate preferentially toward one side. Flat-plate joints are more sensitive to the angle deviation, whereas curved-plate joints exhibit greater sensitivity to the depth deviation.

Accurate measurement of panel and frame poses is essential for achieving automated and high-precision satellite assembly. Feature holes distributed across the satellite's mating surfaces typically serve as assembly and measurement reference points. However, the various types of feature holes, coupled with issues such as high reflectivity, edge occlusion, and surface defects, lead to the limitation of pose measurement accuracy and robustness based on feature holes. To address this challenge, a high-precision component pose measurement method based on stereo vision is proposed. First, a contour splitting and merging method based on geometric structural consistency (GSC) is developed to ensure low noise and high integrity of the contour. Next, to enhance feature-hole recognition accuracy and efficiency, a partitioned weighted sampling and iterative consistency (PWS-IC) strategy is introduced. Finally, to further improve measurement robustness, a component pose estimation method is proposed that effectively reduces the impact of outliers on pose estimation accuracy. Experimental results demonstrate that the measurement accuracy of feature holes reaches 0.03 mm, while the position and attitude estimation accuracy of satellite components attain 0.05 mm and $1.1<^>{\circ } \times 10<^>{-{5}}$ , respectively. Compared with existing methods, the proposed approach achieves substantial improvements in both accuracy and robustness. When applied to satellite assembly, the achieved mating accuracy reaches 0.15 mm, satisfying the technical requirement of 0.2 mm.

Digital Twin (DT) technology is pushing manufacturing toward higher intelligence and adaptability. However, existing DT modeling methods still rely heavily on customization, lacking universality and scalability for assembly-oriented manufacturing systems. To address this limitation, this paper proposes a modular DT control framework that couples graphical interaction with reusable functional modules. Based on the classical five-dimensional DT model, the virtual entity is refined into geometric and physical models, and the service system is expanded into behavior and task models, enabling a clearer description and direct correspondence between system structure and operational logic. A behavior-oriented modeling workflow and a data-mapping mechanism are established to enhance scenario adaptability and reduce modeling effort. A graphical DT modeling platform is developed on top of this framework. Multiple robotic manufacturing prototypes, including robotic drilling, robotic gluing, and hybrid drilling systems, are constructed to assess the generality and reconfigurability of the proposed approach. A drilling experiment is performed on the robotic drilling system to validate the DT-based control execution mechanism. The resulting holes exhibit an average positioning error of 0.23 mm and a diameter error of 0.012 mm, both meeting aerospace drilling requirements. This confirms that virtual task commands can be accurately executed on physical system under the proposed DT framework. Overall, the DT prototype implementations and drilling experiment jointly verify the scalability of the framework and its DT-based control capability, providing a practical approach for the rapid development and deployment of DT prototypes in aircraft assembly systems.

Multi-body separation involving collisions is common in aerospace engineering. The ability to analyze the dynamics of multi-body collisions is rarely possessed by traditional Multi-Body Separation Simulation (MBSS) methods. To methodically address this challenging issue, a research study is conducted herein based on the MBSS in conjunction with an efficient and high-accuracy collision model. First, an MBSS based on the dynamic unstructured overset grid method is performed by solving the unsteady compressible Reynolds-averaged Navier-Stokes equations with the six-degree-of-freedom rigid-body motion. Second, to detect object collisions and calculate collision factors with high accuracy and efficiency, a collision detection approach and a nearest distance calculation based methodology on the basis of computational fluid dynamics data structures and bounding volume hierarchies are originally proposed. Third, a transient multiple collision model is established to simulate an unlimited number of object collisions within a single time step. Finally, collision simulation experiments with balls and those of the space shuttle’s collision with foreign objects are conducted to verify the accuracy, efficiency, and robustness of the newly developed approach.

Taking human-robot collaborative assembly as an example, the methods based on contact forces can improve the assembly efficiency of industrial robots with large components in industrial manufacturing. However, due to the large size, high payload, assembly accuracy and dynamic changes in grip position, accurately estimating the contact forces between the payload and the operator becomes challenging when handling these large components. In this paper, a two-stage method is proposed for payload dynamic parameter identification. The parameter identification equation in the sensor coordinate system is initially established. Furthermore, the identification model of recursive restricted total least squares (RRTLS) based on total least squares (TLS) is constructed to achieve low-consumption online identification. According to the assembly requirements and payload characteristics, the posture coordinate system is designed for safety, including the feasible workspace for the robot. Subsequently, the static identification postures and dynamic excitation trajectory are planned to obtain static values and dynamic inertial parameters. In the end, a high-payload human-robot collaborative assembly system is built to validate the proposed method. Experimental results show that compared with the existing methods, the proposed approach can effectively identify and compensate the payload, leading to more accurate external force sensing.

Due to its excellent mechanical properties and strong process feasibility, CFRP is commonly used to repair damaged aerospace metal components. However, the differences in physicochemical properties among the metal, adhesive layer, and patch often induce curing residual stresses and deformation in the bonded area after forming, which can affect the load-bearing performance of the repaired structure. This study investigates the effects of residual stress and curing deformation. Tensile tests were designed for single-sided CFRP patch repairs on damaged titanium alloy components, and a multi-stage numerical analysis method was established, covering the process from co-curing bonding to quasi-static tensile loading. Through comprehensive analysis of experimental and simulation results, the strain evolution behavior of the adhesive layer during the curing stage was clarified, the stress-strain curves and damage failure modes during the tensile stage were compared, and the influence of curing processes on tensile performance was explored. The results show that the strain in the adhesive layer during curing can be divided into five stages, with a simulation error of less than 20% compared to experimental data. The multi-stage simulation method, which accounts for residual stress and curing deformation, yields stress-strain curves that align more closely with experimental results, achieving an error of only 1.39% in ultimate tensile stress. Additionally, the failure modes of different materials observed in the simulation matched those in the experiments. Regarding curing processes, reducing the heating rate and extending the dwell time improved the curing degree and modulus of the patch and adhesive layer. This also reduced tensile stress and increased compressive stress in the titanium alloy substrate along the loading direction, ultimately enhancing the overall tensile performance of the structure.

Electroadhesion (EA), with its advantages of broad interfacial applicability, switchable adhesion, and low power consumption, is regarded as having prospective applications for the end-effectors of on-orbit spacecraft maintenance robots. However, its reliability in space has been constrained by the planar electrode configurations commonly adopted, which suffer from issues such as low EA force and poor stability. To address this, a three-dimensional (3D) laminated electrode configuration of EA is proposed in this paper. The mechanism for enhancing the EA force in this electrode configuration is revealed through modeling and simulation, leading to the optimization design of its key parameters. An EA force test platform is constructed to systematically compare the EA performances of conventional planar electrodes and the proposed 3D laminated electrodes on different material surfaces (insulator, semiconductor, and conductor). The experimental results demonstrate that the 3D layered electrode configuration exhibits significantly superior EA force compared to planar electrodes, along with enhanced stability. This study provides novel insights and an experimental basis for high-performance EA end-effectors of on-orbit spacecraft maintenance robots.

The in-orbit collision safety and reliability of a spacecraft are directly influenced by the dynamic characteristics of its collision buffer system. A rigid-flexible coupling dynamics model of the collision buffer system was established based on the multibody systems transfer matrix method. The overall transfer equation, characteristic equation, and dynamics response equation of the system were derived according to the topological graph of the dynamics model describing the transfer relationships of each component. Additionally, the vibration characteristics of the system were analyzed through numerical simulations. Modal tests of the collision buffer system were conducted to validate the accuracy of the proposed model. The effects of physical parameters, such as stiffness coefficients on the dynamic characteristics of the collision buffer system were analyzed and the regulatory mechanisms of key parameters on the system’s natural frequencies and vibration responses were revealed. The method established in this study was demonstrated to significantly enhance the efficiency of system vibration characteristic analysis, providing a novel technical approach for the dynamic characteristic analysis and optimal design of spacecraft collision buffering systems.

In industrial robot visual servoing, the accuracy of end-effector pose directly affects the feedback quality and trajectory tracking performance of the visual servo system. To improve end-effector pose estimation accuracy, this paper establishes a propagation model from marker measurement errors to end-effector pose estimation errors and further derives the covariance expression of pose estimation errors. Based on this model, different marker placement factors affecting translational and rotational errors are analyzed, including marker-set spatial range, spatial distribution balance, and centroid offset distance. In addition, the influence of the number of markers on pose estimation errors is derived by adding a new marker to an existing point set. The accuracy of the analytical model is validated through Monte Carlo simulations and experiments, and guidelines for marker placement and marker number are provided.

In high-value manufacturing, dual-robot systems face a fundamental observability paradox: the very scenarios demanding precise cooperation are often those where physical occlusion prevents the dual-sided sensing required to achieve it. This bottleneck severely limits the application of flexible automation in complex tasks such as aircraft assembly. To address this challenge, this study proposes a cooperative control paradigm centered on model-based virtual sensing. This approach leverages a high-fidelity and precalibrated kinematic model of the dual-robot system as a virtual sensor, enabling the precise inference of the occluded robot's target pose using only single-sided physical measurements. We designed, integrated, and validated this paradigm on an industrial-scale dual-robot system for cooperative drilling and electromagnetic riveting (EMR). The experimental results demonstrate that the framework successfully constrains the cooperative attitude error to below 0.4 degrees. Compared to noncooperative methods, it reduces the average height of drilling exit burrs by 69.3% and improves the quality of EMR joints by decreasing the average perpendicularity error of the driven head by 34% and the coaxiality error by 64% . This work presents a robust and cost-effective solution that replaces infeasible or costly physical sensors with model-driven intelligence, advancing the frontier of flexible automation in aerospace manufacturing.

The traditional curve parameter synchronization method cannot constrain the kinematic parameters of the linear motion and the angular motion of the industrial robot at the same time. This may cause sudden changes in angular motion, which in turn leads to vibration of the robot and affects machining quality. Therefore, a real-time synchronous velocity planning method for robots’ smooth trajectories is proposed in this paper to improve the shortcomings of the curve parameter synchronization method. The coordinate parameterization of angular motion is carried out by using the logarithmic quaternion description, which reduces the difficulty of quaternion planning. To avoid iterative interpolation of higher-order curves, the G2 continuous corner smooth curve is constructed by an arc-length parameterized clothoid curve. Based on the S-shaped velocity curve and time synchronization constraints, a time synchronization velocity planning method is proposed to improve the overall interpolation efficiency by avoiding excessive reduction of the start and end velocity of the synchronization segment. By combining independent velocity planning with synchronous velocity planning through the backtracking nesting method, this method not only eliminates the velocity fluctuation problem caused by the time rounding strategy but also realizes the synchronous velocity planning of linear and angular motions of continuous trajectories. Simulations and experiments show that the proposed method achieves more efficient synchronous velocity planning of linear and angular motion, avoids the velocity fluctuation problem caused by time rounding error, ensures that all kinematic parameters are within the constraint range, and effectively reduces the vibration at the end of the robot.