121 results about "Robot kinematics" patented technology

The invention relates to the technical field of robot navigation, and discloses an automatic path-finding intelligent robot and a path-finding method thereof. According to the method, multi-dimensional spatial data including obstacle distribution, ground features and dynamic target motion information is acquired through an environment sensing device, spatial discretization processing is performed on the data, and a topological map which has a hierarchical structure and includes a node connection relation and a region passing weight is generated. Then, according to the node connection relation of the topological map, a path planning model based on manifold learning is established, and an optimal path candidate set is determined by calculating the manifold distance between adjacent nodes; then extracting a key node sequence in the candidate set, dynamically optimizing a path in combination with a region passing weight, and generating a preliminary navigation track; and finally, inputting the initial track into a motion control model, carrying out smooth processing according to kinematics constraint of the robot, and outputting a final execution path. According to the invention, the robot can efficiently find the way in a complex environment.

The invention discloses an assemblage multi-robot collaborative welding system in ship sections, and relates to the technical field of industrial robot collaborative control, the assemblage multi-robot collaborative welding system comprises an industrial internet platform, the industrial internet platform is in communication connection with the following modules: a visual inspection modeling module, which is used for scanning the surface of a workpiece through a 3D camera, constructing a point cloud model, and establishing a point cloud model; matching the point cloud model with a design drawing, and identifying a deviation between an actual workpiece and the drawing; and the path planning and correcting module is used for planning a collision-free welding path in combination with the visual detection data and the motion range of the robot. Through high-precision visual inspection scanning and an SLAM matching algorithm, a workpiece point cloud model is constructed in real time and is accurately aligned with a design drawing, the welding seam position and the workpiece geometric deviation can be accurately recognized, a collision-free welding path is generated in combination with robot kinematics constraint and a safety boundary, it is ensured that the pose of the tail end of a welding gun is attached to the surface of the workpiece, and the welding quality is improved. Welding deviation is reduced, and process stability is ensured.

The invention provides a configuration optimization method before capturing of a space double-arm robot, and the method comprises the steps: constructing a kinematics and dynamics model of the space double-arm robot according to a three-dimensional model of the space double-arm robot; constructing a kinetic model of the to-be-captured target by using the motion parameters of the to-be-captured target in the space; according to the dynamic model of the space double-arm robot, the relative mass of the space double-arm robot under non-centering collision is obtained, and a maximum pre-contact collision force performance evaluation index is constructed; further constructing a double-arm closed chain inertia matching index performance evaluation index; constructing a configuration optimization model before the space double-arm robot captures the target; and through a multi-target optimization algorithm, the optimal configuration of the space double-arm robot before capturing the target is solved. The pre-contact collision force peak value of the double-arm robot during target capturing can be effectively reduced, and meanwhile the operability of a closed chain system formed after capturing is guaranteed.

The invention discloses a multi-constraint path planning method and device based on intelligent heuristic search, and is suitable for a mobile robot in a complex and narrow environment. According to the method, a multi-source sensor is used for environment perception and fusion mapping, and a grid map is generated; a neural heuristic search algorithm based on a Mama structure and a selective state space model (Selective SSM) is adopted on the cost map, and a guide graph is generated; a continuous and collision-free initial path is generated through self-adaptive step size control in combination with robot kinematics constraints and channel characteristics; further establishing a multi-target constraint model based on a robot center Euclidean symbol distance field (RC-ESDF), and executing path smoothing and safety optimization by using a priori-guided particle swarm optimization algorithm (Prior-guided PSO) to obtain an optimal path meeting dynamic consistency; the system corrects the path in real time through a closed-loop feedback mechanism and triggers dynamic re-planning, so that the path feasibility, safety and real-time adaptive capacity of the robot in a limited environment are remarkably improved.

The invention relates to the technical field of spraying control, and discloses a wind power tower wall surface spraying method and system, and the method comprises the steps: scanning a wind power tower wall surface through a sensor, obtaining the surface contour data of the wind power tower wall surface, and forming reference geometric information; curvature distribution characteristics of the reference geometric information are extracted, key path points are extracted according to the curvature distribution characteristics, robot kinematics constraints are introduced to carry out smoothing and coverage completeness integrated processing on the key path points, and therefore a spraying path is generated; establishing a mapping relation between the curvature of the spraying path and nozzle parameters, and setting initial values of atomization pressure and coating flow based on the mapping relation; in the spraying execution process, the real-time thickness monitoring data and the preset thickness are fused to generate a parameter adjusting instruction, and an actuator is driven to conduct online correction on spraying parameters; according to the method, accurate adaptation of the spraying path and the outline of the tower drum and dynamic matching of spraying parameters are achieved, it is ensured that the thickness of the coating always fits the preset standard, and the stability and controllability of the spraying process are improved.

The invention provides a ship active stabilization control method and system, and relates to the field of ships. The ship active stabilization control system comprises a stabilization execution mechanism which comprises an upper platform constructed according to a ship body of a ship and a lower platform constructed according to multiple sets of water pressing plate execution mechanisms, and the multiple sets of water pressing plate execution mechanisms are arranged at any positions below waterlines of the two sides of the ship correspondingly; each water pressing plate executing mechanism comprises a water pressing plate assembly and a driving cylinder connected with the water pressing plate assembly; the data acquisition unit is configured to acquire ship body attitude and motion state information and environment data of the ship; the stabilization controller is configured to calculate and generate correction torque according to the parallel robot kinematic mechanics mechanism model, the ship posture and motion state information and the environment data, and distribute the correction torque to an execution instruction corresponding to each driving cylinder; and the driving cylinders drive the corresponding water pressing plate assemblies to execute water pressing movement or return movement according to the execution instructions.

The invention discloses an agricultural robot trajectory planning method and system with optimal energy consumption under collision constraint. The method comprises the following steps: acquiring historical state sequence data and environmental map information of a target machine and peripheral machines in real time by a self-machine; identifying the operation intention of the target machine, and outputting a multi-modal prediction trajectory; the method comprises the following steps of: generating a global coarse reference track covering an operation area by taking completion of an own operation task as a main target; generating a space-time safety corridor by adopting a space-time inheritance strategy, and reserving a safety space for the dynamic obstacle; constructing an optimization problem cost function, and comprehensively considering reference trajectory cost, collision risk cost and energy consumption cost; and under the boundary constraint of the safety corridor and the kinematics constraint of the robot, solving the optimization problem by using a numerical optimization solver to obtain an optimized local trajectory. According to the method, safe, efficient and energy-saving collaborative operation can be realized by fusing multi-modal trajectory prediction of the dynamic obstacle, refining energy consumption modeling and risk perception planning.

The invention discloses an industrial robot motion pose error calibration method based on constraint solution. The industrial robot motion pose error calibration method comprises the steps that S1, joint angles, tail end coordinates and temperature data of multiple measurement points are collected; s2, correcting the kinematic model by using the thermal elongation and constructing a parameter identification model; s3, constructing a mixed integer nonlinear constraint pool according to mechanical limitation; s4, introducing a semi-definite programming slack variable to convert the non-convex constraint into a linear matrix inequality; s5, combining a primal-dual interior point method and an alternating direction multiplier method to iteratively solve the optimal kinematics parameter correction; s6, introducing a square root information filtering improvement mechanism to correct a state vector square root factor, and calculating an updated nominal kinematics parameter; and S7, based on the condition number of the error Jacobian matrix, judging observability and repeatedly calibrating. According to the method, the problem of precision reduction caused by thermal errors is solved, and the identification precision, the numerical stability and the self-adaptive calibration capability of the kinematics parameters of the robot are improved.

The invention discloses a robot joint positioning method and device and a storage medium, and belongs to the field of robot control. The method comprises the steps of performing article recognition on environment image data to obtain article data, and inputting the article data into a robot motion learning model in combination with joint pose data to perform coordinate transformation calculation to obtain relative position data of an article and a joint; according to the relative position data and robot executable motion data obtained by a joint power parameter table of the robot, adjusting a joint power adjusting coefficient of the robot to generate a robot joint control parameter, and performing dynamic smooth calibration on the joint control parameter to obtain a variable structure control signal; acquiring an impedance control signal according to the object contact force data and the variable structure control signal; carrying out weight merging on the impedance control signal and the variable structure control signal to obtain a joint driving signal; and the joint driving signal is sent to the robot, so that the robot executes corresponding operation according to the joint driving signal.

The invention discloses an inverse kinematics method for a redundant seven-degree-of-freedom robot. The method specifically comprises the following steps: step 1, establishing forward kinematics modeling of the seven-degree-of-freedom robot; step 2, inputting a target pose, and defining a tail end pose error of the seven-degree-of-freedom robot as a Riemannian distance on a three-dimensional special Euclidean group manifold; 3, adopting a three-stage hybrid optimization strategy; 4, carrying out constraint processing between joints; and 5, verifying convergence and robustness. The adaptive differential evolution algorithm is used as a core optimizer, parameters of the adaptive differential evolution algorithm can be dynamically adjusted along with an iteration process, and global exploration and local development capabilities are balanced; and a dynamic parameter adjustment strategy of nonlinear progressive increase of a scaling factor and linear progressive decrease of a crossover probability is designed, and a DE / current-to-pbest variation strategy is adopted, so that the algorithm pays attention to global exploration in the initial stage of iteration and is biased to fine development in the later stage, and the convergence speed and the global search capability are effectively improved.

The application discloses a double-robot path planning method for rocket tank weld detection based on binocular vision, which comprises the following steps: firstly, a measuring instrument and a weighted moving average filter are used to calibrate the kinematic parameters of a robot; then, a Monte Carlo method is used to solve the double-robot collaborative space, so as to determine the range of the double-robot collaborative working interval and the rocket tank products that can be detected; the running area of each joint is determined by using the collaborative working space, the running range of each joint is reset, the double-vision technology is used to reduce the clamping error of the rocket tank to be detected and identify the model of the rocket tank to be detected; in addition, a polynomial interpolation method is used to interpolate and plan the double-robot path, so as to automatically generate the rocket tank path trajectory and the trajectory number corresponding to the model; finally, the communication between the robot control system and the detection software is established, so as to realize the automatic calling of the rocket tank detection path trajectory and the automatic process detection.

The application discloses a hybrid robot kinematics analysis method, which is applied to a hybrid robot and comprises the following steps: acquiring the position coordinates of key points in parallel structure parts in an upper motion platform and a lower motion platform based on a base coordinate system by using a geometric analysis method; acquiring the rotation angles of upper universal joints and lower universal joints; establishing DH models of series structure parts in the upper motion platform and the lower motion platform based on the position coordinates and the rotation angles; determining DH parameter tables of upper models and lower models based on the DH models; solving the pose of a terminal sleeve and a puncture needle based on the DH parameter tables, and obtaining a conversion matrix of any point on the puncture needle relative to the base coordinate system. The application can realize the technical effect that kinematics analysis of the hybrid robot is more efficient, and thus solves the problem that the kinematics analysis method in the prior art is not applicable to kinematics analysis of the hybrid robot.

This invention discloses a method, system, device, and storage medium for generating three-dimensional cutting trajectories, comprising the following processes: acquiring a CAD model of the finished product, extracting cutting trajectory lines, and generating a three-dimensional point cloud of the CAD model; scanning the workpiece to be cut to generate a three-dimensional point cloud of the workpiece; registering the three-dimensional point cloud of the CAD model and the three-dimensional point cloud of the workpiece to be cut, calculating the transformation matrix, and performing coordinate system transformation on the CAD model according to the transformation matrix; generating a set of cutting poses based on the cutting trajectory lines and the transformation matrix, performing translation and rotation adjustments, smoothing, sorting, deformation compensation, and robot kinematics checks on the set of cutting poses to generate a set of cutting trajectories containing multiple cutting trajectories; and generating a cutting program based on a recognizable syntax based on the set of cutting trajectories containing multiple cutting trajectories.

The invention relates to the technical field of robot path control, and discloses a robot path control method based on automatic operation. The method comprises the following steps: acquiring three-dimensional point cloud data of a robot working environment, and generating an environment grid map through spatial rasterization processing; a dynamic obstacle track is extracted based on the map, and a dynamic obstacle avoidance constraint condition is constructed in combination with kinematics parameters of the robot. After the path search space is initialized according to the constraint condition, a candidate path set is generated by adopting a heuristic strategy, and an optimized path meeting a preset threshold value is screened out through smoothness and energy consumption evaluation. And inputting the optimized path into a track generator to generate a continuous motion track of each joint of the robot. And pose deviation is monitored in real time during operation, and track re-planning is triggered if the deviation exceeds a fault-tolerant threshold value. According to the method, the environment sensing precision and the path generation efficiency are improved, and the stable operation of the robot in a complex dynamic environment is ensured.

The invention discloses an industrial robot and environment contact event identification method based on cross-modal learning, and the method comprises the steps: collecting a visual image and a force sense time sequence of the tail end of a robot, and extracting visual features and force sense features through convolution operation and continuous wavelet transformation; a force sense feature driving offset generation network is utilized to calculate a time offset scalar, time dimension deformable convolution is executed on visual features, and time-space accurate alignment of visual and tactile features is achieved; according to kinematics parameters of the robot, kinetic theoretical stress is calculated, a physical residual vector is obtained through difference between the kinetic theoretical stress and actually-measured force, and inertia force interference generated by motion of the robot is eliminated; mapping the physical residual error, fusing the mapped physical residual error with the aligned visual tactile features, and inputting the fused physical residual error into a neural network to identify a contact type; according to the method, a physical consistency constraint and anti-occlusion reconstruction mechanism is introduced in a model training stage, so that the problems that multi-modal data are asynchronous, and the model lacks physical interpretability and visual occlusion are effectively solved, and the accuracy and robustness of event recognition are improved.

This system increases the number of processes that can be automatically annotated, saving labor, and also detects feature areas in images that are not normally detected during processing. [Solution] A robot control device is used, comprising: a coordinate calculation unit that calculates coordinates from data of an object and a robot manipulator in a simulation environment; a first learning model generation unit that generates a first learning model including data of a first estimated position of the object and the robot manipulator in the simulation environment using first teaching data including coordinates on a simulation image; a second learning model generation unit that generates a second learning model including data of a second estimated position of the object and the robot manipulator in real space based on second teaching data generated using data of the object and the robot manipulator in real space; and a robot control unit that controls the operation of the robot manipulator based on the data of the second estimated position.

The invention discloses an obstacle avoidance tracking control method and system for a submarine cable laying robot with input saturation. The method comprises the following steps: constructing a robot kinematics and dynamics model; a tracking error is calculated based on the reference trajectory and the real-time position, and transient and steady-state performance of the error is ensured through a performance constraint function; designing an obstacle avoidance signal based on an artificial potential field method; combining the performance constraint signal, the speed information and the obstacle avoidance signal to design a virtual control law; designing a fuzzy adaptive law to estimate and compensate unknown disturbance and uncertainty of the system; and finally, a saturation auxiliary system is introduced to construct a final saturation control input so as to limit the amplitude of the actuator and reduce the loss. According to the invention, input saturation, external disturbance and model uncertainty can be effectively processed, and high-precision and strong-robustness obstacle avoidance trajectory tracking control is realized.

This application provides a cooperative control method and system for two humanoid robots, relating to the field of robot control technology. The method includes acquiring interaction data from two demonstrators; performing interactive perception motion redirection on the two humanoid robots based on the interaction data to generate a reference trajectory and topological prior that conform to robot kinematic constraints. Specifically, kinematic conflicts arising from heterogeneous redirection are resolved through dual-scale manifold optimization, accurately preserving the interaction intent; using the reference trajectory as the tracking target and guided by the topological prior, reinforcement learning is performed to obtain a cooperative control strategy for the two humanoid robots; the trained cooperative control strategy is deployed to the two humanoid robots, which exchange state information through real-time communication to perform physical cooperative tasks; this significantly improves the robustness of control and training efficiency; and ultimately achieves zero-sample transfer of the cooperative strategy from simulation to real-world operation.

The application provides a flexible joint robot arm tracking control method and device based on an adaptive neural network, and relates to the technical field of robot intelligent control. The method comprises the following steps: establishing a robot kinematics model, defining a trajectory tracking error, and designing a control input based on the robot kinematics model; adopting a neural network compensation model to compensate for model uncertainty, and adopting a disturbance observer to estimate unknown disturbance, so as to obtain an adaptive bounded neural network control based on state feedback; building a robot system platform to verify the feasibility and effectiveness of the method, and defining a Lyapunov function to prove the stability of the closed-loop system. The application constructs an adaptive bounded neural network controller, which can estimate the uncertainty in the model parameters and adjust the controller gain to adapt to the actuator limit, so as to ensure the effective trajectory tracking of the system. Subsequently, in order to further enhance the stability and robustness of the system, the application also designs a disturbance observer to estimate and compensate for unknown external disturbance.

The invention discloses a robot electric arc milling method which comprises the following steps that S1, an electric arc milling hardware system is built, and the hardware system comprises a motion main body part, an electric control part and an auxiliary machining part; s2, constructing a milling off-line programming system, wherein the milling off-line programming system comprises a robot kinematics modeling method, a machining path planning method and a robot operation method; s3, establishing a milling test to obtain target process parameters, wherein the milling test comprises plane milling, curved surface milling and impeller milling; and S4, the target technological parameters are imported into a milling off-line programming system, a hardware system is driven to execute milling operation through a control instruction output by the system, and complex profile machining is completed. The invention provides an electric arc milling method based on a multi-axis robot. Key technical researches such as robot off-line programming and machining process tests are carried out aiming at strong combination of the robot and non-traditional machining.

The invention discloses a six-degree-of-freedom robot inverse kinematics solution solving and selecting method which comprises the following steps: establishing a kinematics model according to DH parameters of a six-degree-of-freedom badminton robot; calculating the origin position of a fourth joint coordinate system; calculating the angle of the first joint; calculating the angle of the second joint; calculating the angle of the third joint; calculating the angle of a fifth joint; calculating the angle sum of the fourth joint and the sixth joint; converting angles of a plurality of solutions of the inverse kinematics into intervals by integrating the solution and the condition that the inverse kinematics has a plurality of solutions; and selecting inverse kinematics by adopting a selection strategy. According to the method, the kinematics model is established based on the DH parameters, all joint angles are solved step by step, the solving process is simplified, error accumulation caused by complex operation is reduced, and the inverse solution solving precision is improved; a possible solution of the inverse kinematics is converted to a specific interval, and weighted evaluation is performed through a systematic selection mechanism, so that the limitation of a traditional method is overcome.

The invention belongs to the technical field of intelligent manufacturing and industrial robots, and particularly relates to a battery assembly robot grabbing method based on deep learning, and the method comprises the steps: constructing a physical support map based on three-dimensional point cloud data, and calculating the metastable state support index of each battery to evaluate the collapse risk; a dynamic shearing safety index is calculated by combining robot kinematics and battery physical attributes, and a grabbed object is prevented from slipping in high-speed movement; the global disclosure gain is evaluated by simulating the grabbing action, the grabbing sequence is optimized, and follow-up grabbing difficulty is avoided; through a multi-target optimization strategy, on the premise of ensuring physical stability and dynamic safety, an optimal grabbing target capable of maximizing subsequent operation convenience is selected. The safety, the efficiency and the intelligent level in the battery grabbing process are improved.

The application discloses a robot integrating an elastic tube liquid transmission mechanism and a continuous robot elastic arm, and relates to the field of robots.The robot comprises a rack (1), an elastic tube (2), support discs, base discs and a driving line (3), the elastic tube (2) is fixed on the rack (1), the elastic tube (2) is divided into multiple arm sections, each arm section is sequentially provided with a base disc and multiple support discs, the interval distance of each support disc is equal, the base disc and the support disc are fixed on the elastic tube (2) through a clamp, multiple through holes are distributed on the support disc, and every three through holes with an interval of 120 DEG form a group.The elastic tube liquid transmission mechanism and the continuous robot elastic arm are integrally designed, an elastic support body does not need to be additionally provided, the robot structure is more compact, the manufacturing cost is lower, and the problem that the prior art cannot well correct the pose error in a robot kinematics solving process is solved.

The application belongs to the technical field of industrial robots, and discloses a wall-climbing machining robot curved surface motion control method and system, which comprises the following steps: (1) establishing a robot kinematics model under the constraint of instantaneous motion plane; (2) regarding the model error caused by the kinematics model uncertainty and external disturbance as an extended state, then constructing an extended state observer to observe the kinematics model error of the robot, and obtaining an error compensation control signal; on the basis of not considering the kinematics uncertainty, establishing a kinematics error state space model of the robot trivial system, and establishing a nonlinear model predictive controller, then solving the optimal control sequence of a cost function to obtain the control signal of the trivial system; (3) calculating the control signal of the closed-loop control system of the robot, and then realizing the motion control of the wall-climbing machining robot on the curved surface in three-dimensional space. The application provides protection for efficient and high-precision machining of the wall-climbing machining robot.

This application belongs to the field of navigation technology, specifically relating to a method, device, system, and storage medium for instrument positioning and navigation. The method includes: acquiring real-time images of an endoscope and preoperative images of the target object; determining a first position transformation model of the endoscope relative to the target object based on the real-time and preoperative images; acquiring a second position transformation model of a fixed base point in the instrument arm relative to the endoscope; determining a third position transformation model of the fixed base point relative to the target object based on the first and second position transformation models; and obtaining the position of the moving node relative to the target object based on the positional relationship between the moving node and the fixed base point in the instrument arm and the third position transformation model. This application improves robot navigation accuracy and avoids safety risks in robot operation by determining the position of the instrument arm relative to the target based on endoscope images and a robot kinematic model, and then performing precise navigation based on the determined position.

The application is a kind of substation inspection robot adaptive trajectory tracking control parameter multi-objective optimization method based on NSGA-Ⅱ, first, the kinematics model of the robot and the path tracking error differential equation are established, second, based on NAGA-Ⅱ algorithm, a multi-objective optimization model in robot trajectory tracking is established, taking the size of tracking error and convergence time as optimization principle, the Pareto frontier of tracking curve with different curvatures is obtained; finally, according to the expected proportion of tracking error size and convergence time set by the substation, the Pareto frontier of the current tracking path is evaluated and analyzed by using the TOPSIS method, and the optimal solution required at present is obtained. The application considers the change of the space center occupied by the inspection robot, improves the tracking accuracy, and simultaneously reduces the size of tracking error and convergence time by using the multi-objective optimization method, which has important significance in improving the intelligence degree of substation inspection robot, increasing the work efficiency, expanding the application range and the like.

Rather than retrofitting an ultrasound probe, the present invention is directed to a novel cohesive ultrasound-robotic probe that enables a novel needle insertion path. The tissue-ultrasound probe contact frequently deforms the prostate gland inducing MRI fusion errors. To minimize deformations, the probe of the present invention uses a side-fire probe and robotic rotation about its axis to scan the prostate in 3D. An additional robotic angulation of the needle allows targeting any gland location. Only 2 degrees-of-freedom are required for prostate biopsy. However, the probe and robot must allow clearance to angle the needle, thus a special probe and Remote-Center-of-Motion (RCM) robot kinematics were developed.

This invention specifically relates to a method and system for planning docking points of a loader robot based on operational constraints, belonging to the field of loader robot operation planning technology. This invention constructs a continuous and computable geometric boundary model of the material pile by extracting boundaries and functionalizing the 3D point cloud data. Furthermore, by identifying the elevation of the working steps and solving for their intersection with the bottom of the material pile, this invention uses the intersection line as the geometric reference for constructing the operational logical coordinate system, achieving standardized re-representation of the point cloud, thereby improving the consistency and stability of boundary function fitting and docking point planning. Combining constraints such as robot kinematics, minimum turning radius, and operational safety distance, a feasible operational zone area that meets accessibility and safety requirements is generated. Based on this, a multi-objective optimization model is constructed, comprehensively considering loading efficiency, path cost, and attitude stability, to perform constraint screening and optimization of candidate docking points, outputting the optimal operational docking position.

The invention discloses a robot mixed impedance control method and system for curved surface workpiece grinding, and belongs to the technical field of robot control, and the robot mixed impedance control method comprises the steps that a preset track of the tail end is generated according to an estimated geometric contour, and expected normal preset contact force is set for grinding; calculating an axial component force set value and a radial component force set value of the contact force in the preset track direction; calculating a force tracking error based on the measured value of the stress sensor, the axial component force set value and the radial component force set value, and further generating a force correction signal; scaling the force correction signal through an impedance factor, and superposing the force correction signal with a preset track to generate a correction track; based on the corrected track and the actual pose feedback, calculating a tail end motion correction amount; and through robot kinematics mapping and a driver, the tail end motion correction amount is converted into a torque instruction of a joint space and output for execution, constant-force grinding of the curved surface workpiece is achieved, and contact type machining operation can be stably and accurately completed.

The invention discloses a multi-robot kinematics self-calibration method and system based on vision measurement. The method comprises the steps that a kinematics model of a whole posture adjusting mechanism is established; the space coordinate of a target spot at the tail end of the wing can be measured through the multi-view vision measurement system; selecting a certain POGO column, controlling the Z-axis to move, controlling the X-axis and the Y-axis to apply force to follow the movement, fixing each axis of the other two POGO columns, recording the movement amount of each axis and the space coordinate of the tail end target spot of the wing at m positions, and calculating the rotating shaft of the wing, namely the connecting line of the centers of the ball heads of the two fixed POGO columns under the movement by an SVD (singular value decomposition) method. Other POGO columns are selected to move, the steps are repeated, and an equation of connecting lines of the centers of the ball heads of the three groups of POGO columns can be obtained. By solving the intersection points of the three groups of straight lines, three ball head coordinate values can be obtained. And through the multiple groups of motion data, establishing an optimization model of the kinematics parameters, and solving to obtain the calibrated kinematics parameters. The method has the advantages of being rapid in calibration and capable of achieving automation, and is suitable for flexible assembly of aircraft wings and fuselages.