163 results about "Motion error" patented technology

The invention discloses a mechanical arm positioning and grabbing method based on machine vision, and relates to the technical field of machine vision and mechanical arm control, the method comprises the following steps: synchronously acquiring RGB-D images of a target scene through a multi-view camera array, and generating three-dimensional point cloud data through data fusion; an improved LSD algorithm and a PnP algorithm are adopted to calculate the initial pose of the target object, illumination distortion is eliminated in combination with the generative adversarial network, and three-dimensional coordinates are output; a mechanical arm motion error transfer model is constructed based on Monte Carlo simulation, and a candidate grabbing scheme set is generated through reinforcement learning; and an optimal grabbing scheme is screened through a preset priority evaluation rule, and a mechanical arm joint movement track and a control instruction set are generated. Through multi-modal data fusion and a nonlinear optimization algorithm, the technical problems of large target positioning deviation and sensitive illumination interference in a complex environment are solved, and the grabbing precision and robustness of the mechanical arm are improved.

The invention provides an industrial robot control system and method. The system comprises a trajectory planning module, a dynamic compensation module, a feedback control module, an execution module, a sensor module and a data storage module. The trajectory planning module generates an expected trajectory of an end effector of the robot; the dynamic compensation module calculates a dynamic compensation torque based on the expected trajectory and a robot dynamics model; the feedback control module generates feedback control torque according to the deviation between the real-time pose data acquired by the sensor module and the expected trajectory; the execution module drives robot joints to move according to the synthesized moment of the dynamic compensation moment and the feedback control moment; the sensor module collects robot joint angle, angular velocity and torque data in real time; the data storage module stores robot dynamic model parameters, control algorithm parameters and historical motion data. High-precision and smooth robot motion control can be achieved, the dynamic response and stability of the system are improved, and energy consumption and motion errors are reduced.

The invention relates to the technical field of two-dimensional motion control, and discloses a high-precision two-dimensional motion error prediction compensation iteration method. The method comprises the following steps: on an operation interface of a motion control system, generating a motion track overview containing a target position sequence and corresponding expected motion parameters according to parameters set by a user, and connecting the motion track overview with an actual motion execution device; measuring the deviation between the actual position and the target position of the motion platform at the current sampling moment, and calculating a motion error vector; constructing a prediction model based on the motion error vector and the expected motion parameter, and predicting a two-dimensional motion error at a future moment through iterative optimization; generating a compensation control instruction according to the prediction result and applying the compensation control instruction to the motion execution device; and monitoring the compensated motion state in real time, updating the prediction model and outputting a compensation log. According to the method, by predicting the error in advance and iteratively optimizing compensation, the two-dimensional motion control precision can be effectively improved, the real-time performance and adaptability of compensation are enhanced, and the method is suitable for a high-precision motion control scene.

The invention discloses a motion error dynamic compensation method applied to a surgical mechanical arm, and belongs to the technical field of surgical mechanical arm control and medical automation. The method comprises the following steps: firstly, acquiring position data of each joint encoder of the surgical mechanical arm, a motor current signal, a position feedback signal of an end effector, load change information and accumulative operation duration in real time; processing the data, fusing the data through adaptive Kalman filtering to estimate a joint dynamic error, inputting a load change rate and an accumulated operation time length into a pre-training error prediction model to output a compensation basic quantity, and fusing the load change rate and the accumulated operation time length to generate a real-time error compensation quantity; and then the compensation amount is superposed to a joint original control instruction to correct motion parameters, and finally the compensated tail end position deviation is analyzed, and a precision identifier or an adjustment prompt is generated and fed back to a control system. According to the method, real-time error compensation is achieved, the compensation precision and working condition adaptability are improved, it is guaranteed that the mechanical arm is stably positioned, and the surgical operation risk is reduced.

The invention discloses a real-time dynamic rendering method and system for holographic interaction display, and relates to the technical field of holographic interaction display and real-time light field rendering, and the method comprises the steps: collecting a multi-modal interaction signal in real time, and dynamically generating an attention thermodynamic diagram through a space-time alignment algorithm; compressible motion primitives in the scene are extracted based on Lie group SE (3) motion manifold analysis; constructing a sparse sampling light field calculation model according to the attention thermodynamic diagram and the motion primitives, and dynamically adjusting the compression ratio; and performing non-rigid deformation correction on a phase error caused by interaction by adopting a dual-channel feedback compensation mechanism. Holographic display is driven based on a multi-mode interaction signal, the motion trajectory prediction precision is improved through Lie group SE (3) motion manifold analysis, and motion errors are reduced; in combination with an attention thermodynamic diagram and a light field compression strategy, optimal allocation of computing resources is realized, and rendering time delay is reduced; the phase error and non-rigid deformation are suppressed through a dual-channel feedback compensation mechanism, the holographic image quality is improved, and the interaction experience is enhanced.

A method and a device for identifying geometric errors of a numerical control (NC) machine tool based on a modified nine-line method. Motion errors between a plurality of rigid bodies of the NC machine tool is superimposed to construct a comprehensive error model based on multibody system kinematics theory and a topological structure of the NC machine tool. Optimization is performed based on the comprehensive error model and a preset fitness function to predict six optimal measurement positions. Six linear measurement trajectories are established respectively at the six optimal measurement positions. The six linear measurement trajectories are each parallel to one of an X-axis, a Y-axis, and a Z-axis. error terms for each of the six linear measurement trajectories are measured to establish a first equation set having six first equations. Geometric error simulation and identification for the NC machine tool are performed based on the first equation set.

The invention provides a double-vector cooperative compensation method and system for a multi-degree-of-freedom motion error of a computer rotating shaft, and the method comprises the following steps: synchronously collecting a translation vector and a rotation vector of the rotating shaft through a sensor, and unifying the data of the translation vector and the rotation vector to the same time-space reference; constructing a coupling error model of translation and rotation vectors, and integrating data of the translation and rotation vectors into a unified six-degree-of-freedom error amount; in combination with a feedforward-feedback mechanism, translation and rotation vector compensation weights are dynamically distributed in a time domain, and a real-time adjustment compensation amount is generated through rolling time domain optimization. The method does not need to depend on a complex parameter identification process of a traditional rotating shaft physical model, six-degree-of-freedom error cooperative compensation can be achieved only through sensor data synchronization and a dynamic optimization algorithm, the method is suitable for computer rotating shafts of different loads and motion scenes, and the motion precision and reliability of equipment are remarkably improved.

The invention discloses a phase ambiguity reduction method based on speckle auxiliary phase tracking, which can accurately correct the motion error in a phase shift image by adding a speckle pattern in a phase shift projection sequence and calculating the sub-pixel projection point displacement between a front frame and a rear frame by using a DIC algorithm, obviously improves the precision of three-dimensional measurement, and improves the accuracy of phase ambiguity reduction. The projection points of the phase shift image are aligned to the same camera coordinate through a remapping technology, so that the motion blur error is effectively reduced, the accuracy of a measurement result is ensured, the projection points are tracked instead of tracking the motion of an object, the motion error with z-direction displacement can be corrected, a wrapped phase diagram is obtained through a phase shift method, and the accuracy of the measurement result is improved. And phase unwrapping is carried out by combining a double-frequency order method and a constant geometric constraint method, so that the accuracy and continuity of phase unwrapping are ensured, and the three-dimensional shape of the object is reconstructed by utilizing a triangulation method.

The invention relates to the technical field of unmanned aerial vehicle visual displacement monitoring, and particularly provides an airborne camera motion correction method in unmanned aerial vehicle visual displacement monitoring, comprising the following steps: installing a monitoring target and two reference targets, and collecting unmanned aerial vehicle visual image data; calculating image point coordinates of two angular points on all targets, image point displacement of a midpoint of the two angular points and scale factors of the targets; the z-axis rotation motion error of the monitoring target is calculated; the z-axis translational motion error of the monitoring target is calculated; calculating x-axis and y-axis rotation and translation motion errors of the monitoring target; and correcting rotation and translation motion errors of the z-axis, the x-axis and the y-axis to obtain an actual displacement result of the monitoring target. The method provided by the invention does not depend on the rotation center when correcting the z-axis rotation motion of the camera, is suitable for the actual situation that the rotation center deviates from the image center, and improves the applicability on the premise of effectively improving the visual displacement monitoring precision of the unmanned aerial vehicle.

The invention relates to the technical field of machine vision detection, in particular to a protein chip automatic quality inspection method based on machine vision and related equipment.The method comprises the steps that parameter information and image data are obtained, communication connection is established, mechanical motion errors are compensated through datum point positioning, images are preprocessed and spliced, and defect types are recognized. And outputting an analysis conclusion and establishing closed-loop feedback and data tracing. According to the method, the protein chip quality inspection automation is realized, the detection precision and efficiency are improved, the problems of large error, low efficiency and data non-traceability in traditional manual detection are solved, and reliable quality control technical support is provided for industrial production.

The invention relates to a reinforcement learning mechanical arm dynamic obstacle avoidance method and system based on past experience. Firstly, an improved SAC algorithm is adopted to construct a neural network; then defining an action space, a state space and a reward function, and performing intensive training on the neural network in combination with an HER algorithm, an experience playback pool and course learning to enable the network to converge step by step; after training, outputting an action to control the mechanical arm, detecting collision and motion errors in real time, and dynamically updating network parameters according to a detection result; and through repeated iteration of environment interaction and parameter optimization, accurate obstacle avoidance of the mechanical arm is finally achieved, and the mechanical arm arrives at the target position. Compared with the prior art, the method has the advantages of high flexibility, high adaptability and the like.

The invention discloses a precision detection and compensation method for an automatic tool setting device, which belongs to the technical field of numerical control machining and comprises the following steps of: calibrating position coordinates of a zero point of a laser tracker in a machine tool coordinate system; moving the machine tool to enable the spindle axis and the zero point of the machine tool tracker to be on the same horizontal plane; obtaining coordinates of a reflector rotation circle center position point d on the automatic tool setting device; setting the zero point of the tracker as f, and rotating a machine tool spindle to enable the axis of the radial motion shaft of the automatic tool setting device to be parallel to the straight line fd; a laser tracker is used for obtaining the distribution rule of mechanical transmission errors on the whole stroke of a radial sliding plate of the automatic tool setting device; and carrying out full-stroke positioning precision and repeated positioning precision compensation on the radial sliding plate of the automatic tool setting device until the movement precision of the radial sliding plate meets the expected precision requirement. According to the method, the measuring laser line of the tracker can be ensured to be coaxial with the measured motion axis to the greatest extent, the influence of the motion error of the rotating shaft of the tracker on the measurement precision is reduced, and high-precision position error measurement and compensation are realized.

The invention discloses a CT scanning bed control method and system based on EtherCAT motion control, and the method comprises the steps: selecting a scanning mode according to a scanning demand, and calculating a motion parameter corresponding to the scanning mode; receiving the scanning mode and the motion parameter information, and converting the scanning mode and the motion parameter information into a motion mode instruction of the scanning bed through TCP protocol processing; receiving the motion mode instruction, and converting the motion mode instruction into an EtherCAT protocol format; and receiving the motion mode instruction in the EtherCAT protocol format, and controlling the scanning bed to act through the servo driver based on the motion mode instruction in the EtherCAT protocol format so as to complete a scanning task. EtherCAT full duplex communication is adopted, so that data transmission is more timely and accurate, and high-speed and stable information interaction is realized; a sine line planning model is introduced, the motion trail of the scanning bed can be accurately planned according to different scanning modes, motion errors and jitter are reduced, and the CT scanning precision is improved.

The invention belongs to the technical field of robot motion control, and relates to a motion error compensation method and system for a surgical robot, and the method comprises the steps: collecting, processing and analyzing the actual motion data of each constraint point and tail end point of a mechanical arm, comparing the actual motion data of each constraint point and tail end point with standard motion data, and calculating the motion error of the surgical robot. Obtaining constraint points and end points which are not in the error range; kinematic models are constructed based on the constraint points and the tail end points of the two mechanical arms, and real-time error compensation amounts of the constraint points and the tail end points are obtained; performing inverse kinematics solution on the corresponding real-time error compensation amounts of the constraint point and the tail end point of the corresponding mechanical arm based on the kinematics model to obtain an inverse kinematics solution result; the inverse kinematics solving result is converted into the corresponding control command, the corresponding action is executed based on the corresponding control command, the difference between the actual action of the mechanical arm and the action corresponding to the control command is reduced, and the surgical action execution precision is improved.

The invention discloses a machine tool precision improving method based on guide rail morphology design, which is characterized in that a mapping relation between the machine tool guide rail morphology and a motion error is determined by analyzing the type and the generation mechanism of the motion error of a machine tool, and a guide rail morphology fitting curve is obtained based on a guide rail processing technology and morphology characteristics. A space error prediction model based on the guide rail morphology is established by adopting a multi-body system theory and a homogeneous coordinate change method, and is compared with space error measured data to obtain a space error correction model meeting the prediction precision. And carrying out guide rail morphology optimization design work to obtain a designed guide rail morphology characterization function, and substituting the designed guide rail morphology characterization function into the corrected space error model to obtain a guide rail morphology scheme beneficial to improving the precision of the machine tool. The shape design of the guide rail is carried out by adopting a digital means, the precision of the machine tool is improved, and the method has the advantages of high operation precision, short development period, low production cost and high universality.

The invention relates to a multi-axis cooperative scanning motion control method and system for high-precision scanning imaging, and relates to the technical field of scanning imaging process.The method comprises the steps that in the scanning imaging process, an imaging mechanism model of light tube-sample-flat plate imaging is constructed based on a ray expected track of a ray source, and a light tube-sample-flat plate imaging model is constructed; and analyzing the expected position of the flat panel detector. Then, according to an expected position and a ray expected trajectory, analyzing a motion error and a coupling relationship between the expected position and the ray expected trajectory, and establishing a coupling influence; and according to the coupling influence, a high-precision synchronous motion controller is constructed. Then, kinematics capability limitation and coupling characteristics of each axis are analyzed, coupling mapping and speed constraint are introduced, and a control instruction of synchronous control is updated through speed correction; and finally, performing high-precision synchronous scanning control on each axis motion controller by using the control instruction. Therefore, the full-coverage detection and high-precision imaging of the detected sample are realized by limiting the motion and constraining a zooming synchronous control mechanism.

The invention provides a motion error compensation method and system for a circumferential synthetic aperture sonar platform, and the method comprises the steps: obtaining the position information of an unmanned platform through a GPS, obtaining the attitude information of the platform through an INS, and obtaining the pitching angle of a sonar array through an attitude sensor; the carrying platform performs circumference surveying and mapping, and synchronously records echo data of a sonar array, longitude and latitude data of a GPS, INS azimuth angle data and underwater attitude sensor data; performing joint processing on the data through a data fusion algorithm to obtain the spatial position and attitude parameters of the platform at each time point, and correcting the position and attitude information of the sonar; and performing phase compensation of the signal by using the corrected sonar pose information, and completing projection imaging and focusing reconstruction of the target area by using a synthetic aperture imaging algorithm. According to the method, the problem of imaging blurring caused by platform position errors and attitude deviations in the existing CSAS imaging process is solved, and the underwater target imaging precision and the real-time performance of the system are improved.

The invention relates to the technical field of robot control, in particular to a five-axis hybrid robot error parameter calibration method based on a ball-bar instrument, which measures pose errors existing in a working space caused by various factors such as self structure errors and measurement errors of a robot by adopting equipment such as the high-precision ball-bar instrument and a circular grating. And the error is mapped to an error model of the five-axis hybrid robot, so that real structural parameters of the five-axis hybrid robot are obtained to compensate a kinematic model, and then the robot is controlled according to a new kinematic model, so that the kinematic error of the tail end of the robot is reduced.

The embodiment of the invention provides a nozzle position calibration method and system of a three-dimensional printer and related equipment, and belongs to the technical field of three-dimensional printers. The method first collects a nozzle image including a first view and a second view of a target printing nozzle. Then, a first direction position of the initial nozzle is determined according to the first view, and a second direction position of the initial nozzle is determined according to the second view. And finally, position calibration is conducted on the target printing nozzle according to the target printing position, the initial nozzle first direction position and the initial nozzle second direction position, so that the target printing nozzle moves to the target printing position. Therefore, by collecting the nozzle images containing the initial positions of the target printing nozzle in the two directions, nozzle position deviation or motion errors caused by separated imaging of views of the target printing nozzle in the different directions are reduced, the initial position of the target printing nozzle can be accurately determined, and the printing efficiency is improved. And the accuracy of position calibration of the target printing nozzle is improved.

The invention discloses a sensor angle optimization method for three-point method rotary table motion error separation. The method comprises the following steps: 1) arranging sensors based on a three-point method error separation principle, and obtaining a weight function G according to a mathematical model of a three-point method error separation technology; 2) screening out an angle combination set A corresponding to the sampling point position of the angle combination of which the weight function modulus value G is not equal to 0; 3) comparing circle contour information obtained by performing error separation calculation on each angle combination in the set A with set circle contour information to obtain an optimal combination; 4) calculating an actual optimal angle combination (alpha, beta) according to the optimal combination and a set sensor error delta theta; the relative error delta f'corresponding to (alpha, beta) is calculated, 5) the relation between the angle error of the sensor and the motion error of the rotary table is obtained according to the delta f 'corresponding to different delta theta, and 6) the optimal angle combination of the three sensors for measuring the error of the target rotary table is obtained according to the obtained relation for the target rotary table.

The invention belongs to the technical field of machine tool control, and particularly discloses a machine tool hydrostatic guideway feeding system motion error compensation method and a storage medium. The method comprises the following steps: measuring and acquiring Z-direction error data of the guide rail; processing the data by Fourier series and fitting a guide rail contour error; inputting load, oil pad geometric parameters and guide rail working parameters; a workbench-guide rail balance equation based on consideration of guide rail contour errors is established, and a Z-direction motion error model perpendicular to the feeding direction of a workbench is calculated to serve as a low-fidelity model; the Z-direction deviation ez'and the coordinate Y of the workbench are measured and obtained to serve as a high-fidelity model; constructing a multi-fidelity model by combining the low-fidelity model and the high-fidelity model based on a CO-Kriging method; and inputting the multi-fidelity model into a numerical control system, reading the position of the workbench in real time, substituting the position into the multi-fidelity model, and calculating and compensating the Z-direction motion error of the workbench. The method has the advantages of being easy to operate, high in compensation precision and good in reliability and flexibility.

The invention discloses an unmanned aerial vehicle-mounted through-wall SAR motion error inversion method based on image sharpness and a GCBP algorithm. In order to solve the problem that SAR images are seriously defocused due to airborne platform motion errors, a traditional self-focusing method is popularized to the field of unmanned aerial vehicle-mounted through-wall SAR, and an accurate unmanned aerial vehicle-mounted through-wall SAR signal model is constructed based on the refraction effect of a wall; motion errors are analyzed from geometric characteristics, frequency dependence characteristics, time-varying characteristics and space-varying characteristics, and an accurate phase error model is constructed by adopting sub-aperture division and sub-band division strategies in combination with a GCBP algorithm; and finally, based on an image sharpness criterion and a motion continuity constraint, realizing accurate estimation of the motion error of the unmanned aerial vehicle-mounted through-wall SAR by adopting a gradient descent method combined with a line search strategy. The actual measurement experiment verifies that the method has good refocusing effect and parameter inversion performance in the field of unmanned aerial vehicle-mounted through-wall SAR (Synthetic Aperture Radar).

This invention discloses a high-precision phase recovery method for tooth surface fringe images during gear rotation. The method first establishes an N-step static phase-shift image dataset of the gear at subdivided rotational positions. When constructing network training data pairs, three image combinations with different position indices and phases satisfying the standard three-step phase shift are selected to generate an input sequence simulating unidirectional rotation and motion errors. The high-precision sine and cosine terms calculated using the N-step static images are used as labels. Secondly, an encoder-decoder deep neural network with a bottleneck layer dual attention mechanism and global residual connections is constructed and trained using an adaptive loss function. Finally, the dynamic image to be tested is input into the network to directly predict the sine and cosine terms, calculating the wrap-around phase without motion artifacts. This invention effectively suppresses motion errors caused by gear rotation, contributing to the high-precision reconstruction of the three-dimensional morphology of the tooth surface.

The invention discloses a motion execution mechanism error determination method and device, equipment and a storage medium. The method comprises the following steps: acquiring instruction data corresponding to a motion control instruction of a motion execution mechanism; collecting displacement data of the motion execution mechanism in the process of executing the motion control instruction; and determining the motion error of the motion execution mechanism according to the instruction data and the displacement data. According to the scheme, an error analysis mechanism based on the instruction data and the actual displacement data is introduced, so that the motion performance of the motion execution mechanism is accurately evaluated and quantified. According to the scheme, the positioning precision and the overall operation stability of the motion executing mechanism can be remarkably improved, and the requirements of scenes such as high-precision industrial automation, robot operation and precision machining can be met.

A material conveying mechanism of a microcapsule pre-coating fastener comprises a material conveying rail, a base, a lifting sliding block, a driving motor set, a wheel disc, a connecting rod, a first intercepting rod and a second intercepting rod, and the first intercepting rod and the second intercepting rod on the lifting sliding block are driven by a crank connecting rod mechanism to be alternately inserted into the two sides of the moving direction of the fastener. And an integrated linkage scheme of the same power source is formed. Compared with the prior art that two sets of air cylinders need to be controlled by programs, hardware needs to be continuously adjusted, and the running state of the hardware needs to be detected, the integrated linkage scheme is simpler and more reliable, and the problem of alternating motion errors is solved.

The application discloses a kind of path planning methods for realizing Z-axis orientation constraint based on mechanical arm SDK, it is related to industrial robot control field, the path planning methods for realizing Z-axis orientation constraint based on mechanical arm SDK, including target positioning, path planning and analysis, split mechanical arm operating track and dynamically solve Z-axis optimal parameter, visual detection and posture real-time adjustment and transport data record analysis, relies on the real-time visual data of positioning detection system acquisition, realizes Z-axis pose dynamic monitoring, based on solving data, call mechanical arm SDK combined with Cartesian planning algorithm, real-time adjustment Z-axis orientation and end handling component posture and speed, can promptly correct motion error, the Z-axis deviation caused by workpiece deviation, combined with moveit2 frame collision detection capability and SDK fast response capability, realize the path planning method for Z-axis orientation constraint, effectively avoid collision risk, improve the stability and security of mechanical arm operation.

The invention relates to the technical field of microelectronic assembly equipment control, and discloses a chip pin alignment calibration method based on machine vision, comprising the following steps: establishing a real-time motion error model representing mechanical positioning errors, and obtaining pin polar coordinates through partition extraction; a tangential margin is deducted from the theoretical region to construct a static tolerance window; performing morphological erosion and parallel simulation on the static window at a multi-stage speed by using an error boundary output by the model, and calculating a full-pin dynamic window geometric intersection; and according to the intersection non-empty state, the optimal speed and the target coordinate are decided, equipment mounting is driven, and thermal drift parameters are updated based on an observation residual closed loop. According to the method, the real-time motion error model containing thermal drift compensation is constructed, dynamic morphological erosion based on the mechanical positioning error boundary value is executed on the static window, the effectiveness of mounting coordinates in different thermal states is guaranteed, and dynamic decoupling of precision and speed is achieved.

The invention discloses a robot motion error compensation device, belongs to the technical field of industrial robots, and aims to solve the problem of low final precision caused by large influence factors of existing error compensation. After the visual identification camera obtains position information, needed transverse and longitudinal movement amounts are calculated, the telescopic mechanism changes the height of the fixed seat, the movable mechanism drives the sliding block to change the position of the poke rod, the driving mechanism rotates the rotary disc, the rotary disc pushes the transverse and longitudinal moving frames to move through the poke rod, and finally the moving disc drives the working part to move. The position between a working part and a workpiece is accurately measured through a visual recognition camera, the error amount can be accurately recognized, then the position of the working part is accurately adjusted through cooperative work of a telescopic mechanism, a distance adjusting mechanism, a rotary disc and an adjusting executing mechanism, and the position error of the executing end and the workpiece is effectively corrected. The machining or assembling precision is improved, so that the product quality is improved.

A device for monitoring a patient determines a set of predicted physiological variables using a model trained from physiological variables collected from the patient. The device receives a set of measured physiological variables and a motion measurement. The device compares the set of measured physiological variables to the set of predicted physiological variables to determine a residual vector. The device classifies the residual vector using a vector motion error based on the motion measurement, and performs an action based on the classification of the residual vector.