46 results about "Kinematic calibration" patented technology

The invention discloses a six-axis industrial robot kinematics calibration method based on sub-space identification, and belongs to the field of robot kinematics calibration. The robot is controlled to carry out three-axis linkage and six-axis linkage and move according to the planned four S-shaped paths and one planar circular path, and the error of the robot at the end effector is obtained through measurement of a QC20-W ball rod instrument. And a sub-space identification method is provided to identify and obtain a robot kinematics error parameter, and the error is compensated to a robot kinematics model, so that kinematics calibration of the six-axis industrial robot is realized. And after calibration, the precision is better than that of a whole six-axis linkage compensation method, and a new method is provided for kinematics calibration of the six-axis industrial robot.

The invention discloses a pose decoupling kinematics calibration method, device and equipment and a storage medium. The method comprises the following steps: constructing a pose decoupling motion model based on an equivalent rotation vector and a rigid body motion transformation rule; a pose error is introduced, pose space decomposition is carried out through the pose decoupling motion model, and a pose error expression and a position equivalent expression are obtained; analyzing the coupling influence of the attitude change on the position according to the attitude error expression and the position equivalent expression to obtain a pose coupling increment; constructing a target decoupling calibration model according to the pose coupling increment and the initial decoupling calibration model; and adopting a least square method to carry out geometric error solution of different degrees of freedom on the target decoupling calibration model according to the preset axis pose error to obtain a calibration error. The technical problem that the calibration and compensation effects are poor due to the fact that the influence of the posture in a multi-degree-of-freedom motion system on the position is not considered in the prior art and the error difference between different degrees of freedom is difficult to eliminate can be solved.

Disclosed is a three-dimensional reconstruction method based on kinematic calibration of line structured light point set individualization, and the method includes the following steps: rigidly assembling an area-array camera and a line structured light emitter, and mounting the assembly on a motion platform; calibrating structural parameters of the motion platform of a measuring device by using a reference radius of a standard sphere and line structured light scanned data; registering a spatial position relationship of a line structured light point set by taking a calibrated spherical center position of the standard sphere and the reference radius of the standard sphere as constraints; controlling the five-axis motion platform to move and acquiring scanned data of a measured member under different poses; and completing high-quality three-dimensional model reconstruction of the measured member subjected to multi-pose scanning by using the scanned data and a real-time point cloud registration matrix.

The invention provides a distance identification-based crane tube kinematics calibration method, system and equipment and a medium, and belongs to the technical field of crane tube positioning, a crane tube joint coordinate system and a mechanical arm kinematics model are constructed, differential motion error components generated by each joint coordinate system are transmitted and synthesized step by step, and a mechanical arm kinematics calibration model is constructed. Obtaining a mapping relation between the space error and the kinematics parameter error and the pose deviation of each joint; the loading arm is driven to execute multi-attitude composite motion; target features at different distances and inclination angles are extracted and positioned; establishing a mapping relation between image pixel coordinates and three-dimensional space coordinates, and calculating the depth and coordinates of the target point in the three-dimensional space; and fusing the tail end pose error model and a target actual measurement space coordinate to realize nonlinear optimization and stable convergence of parameter correction. The motion deviation of the end effector is effectively compensated, and the positioning precision is improved. According to the method, calculation of a coordinate system transformation matrix is bypassed, and calibration complexity is reduced.

The invention relates to a parallel robot calibration method, aims to provide a parallel robot compensation method combining data driving with a few-parameter error model, and aims to solve the problems of difficulty in error modeling of a parallel robot with a complex structure and geometric errors and non-geometric errors of residual parts which cannot be identified after traditional kinematics calibration. According to the technical scheme, the method comprises the steps that 1, a closed-loop vector method is used for conducting kinematics analysis on the parallel robot of the complex structure to obtain an inverse kinematics model; 2, establishing a few-parameter geometric error model for the inverse kinematics model by adopting a vector differential method; 3, selecting a least square method optimization function to carry out parameter identification on the parameters of the small-parameter geometric error model; 4, carrying out a kinematics calibration experiment, and updating a parameter identification result to eliminate part of geometric errors; 5, historical data of a calibration experiment are collected, and a Gaussian process regression machine learning model is used for parameter selection and model training; and 6, carrying out prediction compensation on residual unrecognizable geometric errors and non-geometric errors after calibration.

Disclosed in the present invention is a three-dimensional reconstruction method based on kinematic calibration for the monomerization of a line-structured light point set. The method comprises: rigidly combining an area-array camera with a linear-line-structured light emitter, and mounting same on a motion platform; using a standard radius value of a standard sphere and line-structured light scanning data to calibrate structural parameters of the motion platform of a measurement apparatus; with the calibrated spherical center position of the standard sphere and the standard radius of the standard sphere as constraints, calibrating a spatial position relationship of a line-scanned point set; controlling the motion of the five-axis motion platform, and acquiring scanning data of a measured piece in different poses; and using the scanning data and a real-time point cloud calibration matrix to complete high-quality three-dimensional model reconstruction of the measured piece from its multi-pose scanning. The system comprises: an apparatus fixing module, a calibration module, a point cloud calibration module, a scanning module, and a point cloud reconstruction module. By means of using the present invention, the reconstruction accuracy of a line-structured light three-dimensional point cloud model can be improved. The present invention can be widely applied to the field of three-dimensional reconstruction.

The invention discloses a series robot calibration algorithm based on an index product, and the algorithm comprises the following steps: A1, building an index product motion model according to a robot joint axis and coordinate points on the axis through an index product modeling method, a2, differentiating the positions of the robot hand-eye, the kinematics and the calibration object relative to the robot base coordinate system to obtain a hand-eye, kinematics and calibration object position error model based on an exponential product; b1, obtaining an initial value of a robot system hand-eye matrix # imgabs0 # and an initial value of a calibration object relative to the position Bp of a robot base through a closed solution method based on a Kronecker product; b2, taking the difference between the predicted value and the measured value of the base position of the calibration object under the robot base as a target function; and B3, establishing an optimization algorithm by taking the hand-eye, kinematics and calibration object position parameters of the robot as to-be-optimized parameters, and carrying out iterative optimization calculation on the hand-eye, kinematics and calibration object position parameters of the robot by using a Newton iteration method.

The invention discloses a series-parallel robot kinematics calibration method for working area optimization. The method comprises the following steps: analyzing a geometric error source influencing the tail end precision of the hybrid robot, and establishing a kinematic model containing error terms; a laser tracker is used for collecting the difference value between the real coordinates of the tail end point and the output coordinates of the error model in the reachable range of the hybrid robot to generate a residual function; according to the distribution of the measurement points in the working area in the maximum reachable range of the hybrid robot, weighting operation is carried out on the residual function, and an improved particle swarm algorithm fitness function is generated; using an improved particle swarm algorithm to iteratively identify geometric errors of the hybrid robot; the identified error is compensated to a controller, and kinematics calibration of the robot is completed; the kinematics calibration method provided by the invention is simple and efficient, and can be applied to most parallel and hybrid robots.

Example methods and systems for kinematic calibration of a treatment couch for radiation therapy are described. In one example, a computer system may generate and send first instruction(s) to cause the treatment couch to move towards each of multiple calibration poses. The treatment couch may be associated with a kinematic model. The computer system may determine multiple measured poses that are associated with the respective multiple calibration poses. Next, the computer system may determine geometric correction data for updating the kinematic model based on the multiple measured poses. The computer system may then generate and send second instruction(s) to update the kinematic model associated with the treatment couch based on the geometric correction data.

The invention relates to the technical field of robot control, in particular to a kinematics calibration and measurement pose optimization method for a motion redundancy parallel mechanism, which comprises the following steps of: performing error modeling including redundant error parameters on the basis of inverse kinematics of a motion redundancy parallel mechanism, and then designing a parameter identification algorithm to obtain an optimal measurement pose. According to the method, the divergence problem in the identification process is effectively prevented, and the influence of the measurement error on the identification result is reduced as much as possible.

The invention relates to the technical field of intelligent robots, in particular to a multi-robot multi-mode arm-hand-eye relation intelligent calibration method based on online reconstruction-rendering-matching. Comprising the following steps: controlling multiple robots of which the calibration relationship is to be confirmed to move under a configuration sequence for calibration; establishing an online three-dimensional model of each robot according to the online joint angle and kinematics calibration of each robot and the three-dimensional model of each connecting rod of the robot; generating respective two-dimensional images according to the initial hand-eye calibration relationship, the initial arm-eye calibration relationship and the initial arm-arm calibration relationship in combination with an online three-dimensional model, comparing the respective two-dimensional images with respective corresponding actual images, and optimizing according to differences obtained by comparison to obtain a calibration result; and obtaining an accurate hand-eye calibration relationship, an accurate arm-eye calibration relationship and an accurate arm-arm calibration relationship. The invention provides a multi-robot multi-mode arm-hand-eye relation intelligent calibration method based on online reconstruction-rendering-matching, and the robot can be accurately calibrated.

The present application relates to the medical robot control and precision testing technical field, especially related to a kind of kinematics parameter closed-loop calibration method and device of surgical robot end effector.The method is first set up reflection unit on surgical robot end effector, and the motion data of driving unit and the light spot position data detected by photoelectric detection unit are collected;Control surgical robot end effector executes rotary scanning movement to carry out coordinate correction to light spot position data;Each independent motion axis of surgical robot end effector is driven respectively, and according to the mapping relationship of corrected light spot position data and motion data, the transmission parameter and hysteresis parameter of each independent motion axis are identified;Drive the motion axis with coupling relationship, identify inter-axis coupling coefficient, and configure kinematics calibration model to control system.The present application effectively eliminates steel wire transmission coupling and system geometric error through step-by-step optical feedback and geometric self-calibration, and improves the operation precision of end effector.

The invention provides a sub-closed-loop-containing robot kinematics calibration method and device based on constraint relaxation, and relates to the technical field of robot calibration, and the method comprises the steps: carrying out the decomposition of a main kinematic chain under the condition that there are multiple branches in the main kinematic chain of a robot, so as to generate multiple virtual kinematic chains; according to kinematic parameters and closed-loop geometric constraints of virtual joints in each virtual kinematic chain, the theoretical tail end pose of the robot is determined; parameter errors are determined according to the pose deviation between the theoretical tail end pose and the actual tail end pose of the robot; according to the parameter errors and the calibrated kinematics parameters, the corrected pose deviation is determined; and the active joint displacement is updated according to the corrected pose deviation until the corrected pose deviation or the active joint displacement meets the iteration termination condition, the robot is calibrated according to the determined active joint target displacement, and the calibration precision of the robot is improved.

This invention discloses a kinematic calibration method for hybrid robots with optimized working areas. The method includes: analyzing geometric error sources affecting the end-effector accuracy of the hybrid robot and establishing a kinematic model containing error terms; using a laser tracker to collect the difference between the actual coordinates of the end-effector and the output coordinates of the error model within the reachable range of the hybrid robot to generate a residual function; weighting the residual function according to the distribution of measurement points in the working area within the maximum reachable range of the hybrid robot to generate an improved particle swarm optimization (PSO) fitness function; using the improved PSO iteratively to identify geometric errors in the hybrid robot; and compensating the identified errors to the controller to complete the robot's kinematic calibration. The kinematic calibration method proposed in this invention is simple and efficient, and can be applied to most parallel and hybrid robots.

The present invention discloses a robot calibration method based on FIS theory, comprising the following steps: measuring the robot end position error screw based on a laser tracker; establishing the robot's kinematic error model based on FIS theory; identifying the joint axis parameters based on the least squares method; converting the joint axis error into the active joint angle error for error compensation. In view of the problems existing in the existing kinematic calibration methods, such as the unintuitive interpretation of the error source, unclear error identification influencing mechanism, and inconvenient kinematic calibration process, the present invention systematically conducts research on error modeling and identification based on the finite instantaneous screw theory, and establishes a robot error model that meets the conditions of completeness, continuity, and minimization. In the error compensation stage, the present invention converts the identified joint axis error into the driving joint motion, thereby realizing efficient error compensation without changing the control system model. The present invention has high calibration accuracy, simple operation, and strong applicability.

The present invention discloses an optimal index for accuracy measurement configuration of numerical control equipment and its kinematic calibration method, belonging to the technical field of kinematic calibration design of industrial robots, including S1, establishing a geometric error transfer model of the target robot and screening parameters to be identified; S2, establishing a new index based on the ill-condition theory of matrices and the spatial analysis theory; S3, using the new index as the fitness function of the genetic algorithm to obtain the optimal configuration for parameter identification; S4, using the regularization method to obtain the identification result of geometric error parameters; S5, selecting verification configurations in the full working area for error compensation; The present invention first uses the POE method to establish a geometric error transfer model of the robot and screen identification parameters, then discretizes the working space of the robot and uses it as the optimization range of the genetic algorithm, uses the new index as the fitness function to find the optimal configuration, and finally uses the regularization method for parameter identification. By making a comparative analysis with the previous observability index, the superiority of the new index is revealed.

The present invention provides a robot kinematic calibration method, device and electronic equipment, which establishes a measurement coordinate system in the workspace where the robot is located, sets a distance sensor at its origin, and sets encoders on two mutually perpendicular coordinate axes. The robot is moved to multiple calibration positions by teaching. Based on the distance between the distance sensor and the robot and the rotation angle of the robot relative to the corresponding coordinate axis detected by each encoder, the absolute position of the calibration position in the measurement coordinate system is determined. Based on the absolute positions of multiple calibration position points, the calibration of the kinematic calibration model and the calibration of the transformation relationship between the measurement coordinate system and the robot base coordinate system are realized. This solution uses a distance sensor for distance measurement and two vertically arranged encoders to realize rotation angle measurement. It can measure the absolute position of each calibration position point and then realize kinematic calibration, and can obtain better calibration results with a simple model.

This invention discloses a method for determining the structural error during kinematic calibration simulation of a parallel mechanism, applicable to the calibration of industrial parallel robots. The method involves establishing structural constraint equations for the parallel mechanism to determine independent variables in the structural parameters; combining the structural constraint equations and independent variable values ​​to calculate the values ​​of non-independent variables in the structural parameters; calculating the motion of each prismatic joint under ideal structural parameter conditions with a given target pose, establishing the correlation between pose parameters and motion; given an initial structural error value, calculating the structural error value conforming to geometric constraints using constraint equations and nonlinear least squares method, and calculating the norm of the residuals. If the residuals meet the requirements, the structural error for kinematic calibration simulation of the parallel mechanism can be generated; if the residual value does not meet the requirements, the generated structural error is used as input, and a new structural error value is generated again using constraint equations and nonlinear least squares method, and the residual calculation is repeated until the residual value meets the requirements, thus generating a structural error that meets the requirements and accurately verifying the structural error identification accuracy of the error model.

Disclosed are a pose decoupling kinematics calibration method, device and apparatus, and a storage medium. The method includes the following steps: constructing a pose decoupling motion model based on an equivalent rotation vector and a rigid body motion transformation rule; introducing a pose error, and carrying out pose space decomposition through the pose decoupling motion model to obtain an orientation error expression and a position equivalent expression; analyzing a coupling influence of an orientation change on a position according to the orientation error expression and the position equivalent expression to obtain a pose coupling increment; constructing a target decoupling calibration model according to the pose coupling increment and an initial decoupling calibration model; and solving geometric errors in different degrees of freedom for the target decoupling calibration model according to a preset axis pose error by a least square method to obtain a calibration error.

The present application relates to a robot kinematics calibration method based on truncated total least squares regularization, and a parallel robot is provided with a data acquisition system, including a moving platform, a base, a branch chain and a linear motor. The method comprises: obtaining the kinematics parameters of the parallel robot, inputting the inverse kinematics parameter error model, obtaining the conversion error between the coordinate systems and the mapping relationship between the kinematics parameter errors, obtaining the measurement data of the data acquisition system and the conversion relationship between the coordinate systems, making the measurement data uniform in the base coordinate system, identifying the parameter error through the truncated total least squares regularization method, optimizing the selection of the truncation factor, obtaining the best regularization parameter, and compensating according to the identified parameter error to update the controller kinematics parameters. The present application designs a complete low-cost and mature calibration scheme for most parallel robots, which can improve the kinematics calibration accuracy of the parallel robot.

A pose-decoupled kinematic calibration method, apparatus and device, and a storage medium. The method comprises: constructing a pose-decoupled motion model on the basis of an equivalent rotation vector and a rigid body motion transformation rule (101); introducing a pose error, and performing pose space decomposition by means of the pose-decoupled motion model to obtain an orientation error expression and a position equivalent expression (102); analyzing the coupling effect of an orientation change on a position on the basis of the orientation error expression and the position equivalent expression so as to obtain a pose coupling increment (103); constructing a target decoupled calibration model on the basis of the pose coupling increment and an initial decoupled calibration model, wherein the initial decoupled calibration model is constructed on the basis of the pose-decoupled motion model (104); and using the least squares method to perform geometric error calculation of different degrees of freedom on the target decoupled calibration model on the basis of preset axial pose errors, so as to obtain a calibration error (105). The method can solve the technical problem in the prior art that the influence of an orientation on a position in a multi-degree-of-freedom motion system is not considered, making it is difficult to eliminate an error difference between different degrees of freedom, and thus resulting in poor calibration and compensation effects.

The present application relates to a kind of error compensation methods, the purpose is to provide a kind of 2PRU-PSR parallel robot error compensation method, this method has the characteristics of low cost, high efficiency and real-time nature.The technical scheme is a kind of 2PRU-PSR parallel robot error compensation method, according to the following steps:step one: using closed loop vector method to establish the inverse kinematics model of 2PRU-PSR parallel robot and using Newton iteration formula to calculate to obtain complete forward kinematics model;Step two: set error parameter, utilize vector differential method to construct 2PRU-PSR parallel robot error mapping model;Step three: complete kinematic parameter identification and calibrate simulation to verify the correctness of the model built;Step four: using the nonparametric model based on neural network to the end of 2PRU-PSR parallel robot after kinematic calibration remaining error is predicted, using nonparametric model to predict error to complete compensation.

A kinematic calibration and positioning error compensation method that takes into account the deformation of the mechanism can be used to improve the accuracy of robot positioning operations. The deformation is calculated using the superposition method, and the deformation difference is calculated in combination with finite element simulation analysis. The numerical analysis software is used to fit the interpolation curve to establish a deformation model; based on the deformation model, the particle swarm algorithm is used to calculate the corresponding posture error. Based on the multi-body dynamics modeling analysis, the force acting on the telescopic rod ball joint and the friction force at the follower moving pair are analyzed to further calculate the corresponding posture error. The posture errors are added together to obtain the posture error caused by elastic deformation. During the calibration test, the posture error caused by the structural error is separated from the posture error caused by the elastic deformation of the mechanism to improve the identification accuracy; during the error compensation, the posture error caused by the deformation of the mechanism is considered, and the target posture is re-positioned to improve the compensation accuracy; further, a machine learning method is used to establish a correlation between the target positioning posture and the motion of the moving pair. The method of the present invention is simple and easy to implement, which is conducive to improving the accuracy of robot operations and meeting the accuracy requirements of intelligent assembly.

The present invention discloses a three-dimensional reconstruction method based on the kinematic calibration of a single-line structured light point set. The method includes: rigidly combining a planar array camera with a one-dimensional line structured light emitter and installing them on a motion platform; using the standard value of the standard ball radius and the line structured light scanning data to calibrate the structural parameters of the motion platform of the measuring device; taking the position of the center of the calibrated standard ball and the standard radius of the standard ball as constraints to calibrate the spatial position relationship of the line scan point set; controlling the five-axis motion platform to move and obtaining the scanning data of the measured part at different poses; using the scanning data and the instant point cloud calibration matrix to complete the high-quality three-dimensional model reconstruction of the multi-pose scanning of the measured part. The system includes: a device fixing module, a calibration module, a point cloud calibration module, a scanning module, and a point cloud reconstruction module. By using the present invention, the reconstruction accuracy of the three-dimensional point cloud model of the line structured light can be improved. The present invention can be widely applied to the field of three-dimensional reconstruction.

The invention discloses a kinematics parameter compensation value determination method and device, equipment, a medium and a product. Joint angles of all joints of the robot at the current moment are obtained; for each joint, based on the joint angle of the current joint, a preset parameter transition device corresponding to the kinematics parameter of the current joint is used for determining a target compensation value of the kinematics parameter so as to control the robot to move, and the preset parameter transition device is determined based on the first compensation value and the second compensation value; the first compensation value is the compensation value of the kinematics parameter determined when the target joint of the robot is located at a first preset position in the preset positive direction, and the second compensation value is the compensation value of the kinematics parameter determined when the target joint of the robot is located at a second preset position in the preset negative direction. According to the method, under the condition that the motion space and flexibility of the robot are not limited, the precision consistency of the robot in different stress areas is guaranteed, a complex rigidity kinematics model does not need to be constructed, and the practicability of kinematics calibration is effectively improved.

The present invention discloses a method for zero-position fitting and kinematic modeling of mechanism axis integrating measurement point uncertainty, including measuring the coordinates of target points at multiple positions when each axis of the mechanism moves; calculating the length of the semi-major axis, moment of inertia and product of inertia of the point uncertainty ellipsoid; integrating the uncertainty ellipsoid to fit the direction vector of the linear axis of the mechanism in the zero-position state; integrating the uncertainty ellipsoid to fit the plane where the point rotation trajectory is located, measuring the projection of the point onto the plane, minimizing the sum of the squares of the difference between the square of the distance from each projection point to the center of the circle and the square of the radius of the arc, fitting to obtain the position and posture of the rotating axis in the zero-position state of the mechanism; the fourth-order homogeneous transformation matrix corresponding to the movement of each axis is combined with the composition form of the mechanism to establish the conversion matrix from the end coordinate system of the mechanism to its zero-position reference position and posture. It can effectively avoid the convergence problem of parameter identification in the traditional method when the kinematic parameter error is large, so that the kinematic calibration method is applicable to the situation where the position and posture of the mechanism axis are arbitrary.

The application provides a kinematic calibration method and system for a redundant drive over-constrained parallel robot, comprising: constructing a companion error model of each branch of the ROPR by using an exponential product method; describing motion deviation of a redundant joint angle in the error model, and treating deviation of a non-redundant active joint angle as zero; establishing an error feasible space based on a configuration constraint equation; eliminating joint motion error by using a projection method, and establishing an error matrix of the ROPR; measuring end position and posture error of the robot by using a laser tracker; identifying error parameters of the ROPR by using a least square method; and determining drive input of the ROPR according to the identified parameters and performing error compensation. The kinematic calibration method has universality and is easy to be popularized to other redundant drive parallel robots. The kinematic calibration method starts from inherent characteristics of the redundant drive over-constrained parallel robot, and ensures rationality of the error model.

The invention discloses an industrial robot distance residual error modeling compensation method based on PSO-XGBoost. The method comprises the steps that M actual positions of an industrial robot are collected; according to joint information displayed by a robot controller, a homogeneous transformation matrix equation from a robot tail end coordinate system to a base coordinate system is established, and a nominal position from the robot tail end coordinate system to a robot base coordinate system is calculated, called a first nominal position for short; an industrial robot distance error model is constructed, the robot is calibrated, and robot joint parameter errors are obtained; compensating the robot joint parameter error into a robot controller to obtain a compensation distance after kinematics calibration and a compensation distance error after kinematics calibration; establishing a robot residual error model according to the robot joint parameter error; obtaining input parameters according to the robot residual error model; a PSO-XGBoost model is adopted to predict the compensation distance error after kinematics calibration, and the predicted compensation distance error after kinematics calibration is obtained; and compensating the kinematics calibrated compensation distance according to the predicted kinematics calibrated compensation distance error to obtain a residual error compensated distance. Through a double-stage compensation mechanism of model driving and data driving, the precision bottleneck of a single calibration method is broken through, and the distance precision of the industrial robot is improved.

This invention relates to the field of force-position coordinated impedance control technology, and particularly to a force-position coordinated control method for compliant assembly of aircraft fuselage frames. The method includes steps such as kinematic calibration of a CNC positioner, calibration of the installation direction of the force sensor at the positioner's end effector, dynamic modeling of the fuselage bulkhead and linear response analysis of the fuselage web, trajectory planning for the fuselage bulkhead attitude adjustment and positioning process, design of the positioner control law for the fuselage bulkhead attitude adjustment and positioning process, and design of the positioner control law for the fuselage bulkhead and web mating process. Compared to traditional kinematic accuracy compensation strategies based on error differential transformation, this invention establishes a positioner kinematic model based on fitting the CNC positioner axis and hinge joint zero position using spatially measured points. This model requires no design information from the positioner, is applicable to any geometric error of the positioner, and achieves coordinated optimization of the positioning accuracy of the fuselage bulkhead during fine-tuning and the contact force between it and the fuselage web, possessing the ability to perform comprehensive optimal control of force and position.

The present application discloses a posture decoupling kinematic calibration method, device, equipment and storage medium, the method includes: constructing a posture decoupling motion model based on equivalent rotation vectors and rigid body motion transformation rules; introducing posture errors, performing posture space decomposition through the posture decoupling motion model, and obtaining posture error expressions and position equivalent expressions; analyzing the coupling effect of posture changes on positions based on the posture error expressions and position equivalent expressions, and obtaining posture coupling increments; constructing a target decoupling calibration model based on the posture coupling increments and the initial decoupling calibration model; using the least squares method to solve the geometric errors of different degrees of freedom for the target decoupling calibration model based on the preset axis posture errors, and obtaining calibration errors. The present application can solve the technical problems that the prior art does not consider the influence of posture on position in a multi-degree-of-freedom motion system, and it is difficult to eliminate the error differences between different degrees of freedom, resulting in poor calibration and compensation effects.