141 results about "Robot calibration" patented technology

The invention discloses a time stretching sweep frequency interference high-precision distance measurement method and device based on double auxiliary interferometers, and relates to the technical field of non-cooperative target absolute distance measurement. In order to solve the technical defects that in the prior art, due to initial wavelength fluctuation of a light source and frequency sweeping nonlinearity, drift of a ranging result is large, and interference signals are interfered by zero-frequency noise, the technical scheme provided by the invention comprises the following steps: acquiring linear frequency modulation optical signals output by a common-source frequency sweeping laser; the signals are respectively transmitted to a measurement interferometer, an auxiliary interferometer and a resampling auxiliary interferometer to form a homologous three-interference structure; a dispersive medium is introduced through the reference arm, so that the reference light generates time stretching and interferes with the measurement light to form a chirp beat frequency signal; k-domain resampling and cross-correlation processing are carried out on the beat frequency signals, and target distance information is extracted. The method is suitable for high-precision and wide-range non-cooperative target absolute distance measurement work, and is especially suitable for the fields of laser radar three-dimensional modeling, precision industrial detection, robot calibration and the like.

The invention relates to the technical field of joint robot calibration, in particular to a robot motion indication light spot position rapid acquisition device based on four PSDs, and aims to solve the problem that in an existing joint robot calibration device based on the PSDs, it is difficult to adjust a robot to be aligned to the central points of the PSDs. The second PSD is fixed above the first laser reflection structure, the third PSD is fixed below the second laser reflection structure, and the fourth PSD is fixed above the second laser reflection structure. The first laser reflection structure and the second laser reflection structure are fixed to the reference plate, the reference plate is connected with the lower shell through bolts, a power source, a signal processor and a wireless transmitter are fixed in the lower shell, the signal processor and the wireless transmitter are connected with the power source, and the wireless transmitter and the wireless data transmission radio station conduct transmission through wireless communication. And the wireless data radio station is connected with the upper computer. The problem that laser ray constraint must be aligned with the center of the PSD for repeated adjustment is solved, the operation difficulty is reduced, and the calibration efficiency and precision are improved.

A method for calibrating a robot is disclosed. A working space of the robot at least partly overlaps with a working space of a machining and / or production tool. The robot is moved such that a reference point of the robot is at a first position within the working space of the machining and / or production tool. A first position value for the robot at the first position is compared with a first position value for the machining and / or production tool at the position. If the first position value for the robot differs from the first position value for the machining and / or production tool, the first position value for the robot is corrected or the first position value for the machining and / or production tool is corrected such that the first position value for the robot and the first position value for the machining and / or production tool are the same.

The invention provides an industrial robot calibration method and device based on a dial indicator, and the method comprises the steps: collecting the position data of the tail end of a mechanical arm through the dial indicator, and carrying out the preprocessing of the position data of the tail end of the mechanical arm; calculating the tail end position error of the mechanical arm based on the tail end position data of the mechanical arm, and determining an error threshold value and a training iteration round number upper limit; initializing a DH parameter of the mechanical arm, and setting an iteration round number control variable; judging whether the current DH parameter updating meets an updating condition or not; judging whether the iteration round number control variable is greater than a training iteration round number upper limit or not; if the DH parameter meets the updating condition and the iteration round number control variable does not exceed the training iteration round number upper limit, a robot calibration model composed of the robot DH parameter and the joint angle is constructed; and calibrating the DH parameters of the mechanical arm by using an LM algorithm based on the robot calibration model. According to the method, the precision and efficiency of robot calibration are remarkably improved by introducing the elastic equilibrium factor and self-adaptive parameter control.

Robot calibration is crucial in multi-robot cooperative systems where the inaccuracy of robots can add up and cause large errors in the final trajectory of handled parts or process tools. In this work, a two-step calibration approach is proposed based on artificial neural networks (ANNs) and definition of compensated pose for a master-slave cooperative robot system. Measuring the pose of master and slave robots at different locations in their shared workspace is required to create pairs of joint angles and output pose errors as training data. The generated data is used to train two ANN models for compensating the master-slave relative error and the master robot errors. The master-slave relative error is corrected by introducing a compensated pose for the slave robot with respect to the master robot. A neural network is then trained to predict the error parameters of the compensated pose for the joint angles of both robots as the input. The master robot is then corrected individually using another ANN model to address the absolute accuracy of the cooperative system.Measurements and simulations have been performed on a dual-robot cooperative system before and after geometric calibration. The process of cross validation is carried out to find the best network architecture for the optimal performance in correcting the robots'errors. It has been shown that even after pre-existing model-based calibration of each robot, both the absolute accuracy of the master robot and the relative tracking accuracy can be further improved by the proposed implementation of ANN calibration.

The invention relates to a double-robot automatic calibration method based on self-adaptive point location planning in a restricted space, and belongs to the technical field of double-robot calibration, and the method comprises the steps: building a three-dimensional simulation model of a double-robot operation space on an Rviz platform based on an ROS architecture; a collision detection module is used for randomly generating a calibration point composed of collision-free double-robot joint angle vectors; when the robot is driven to move, data of the motion capture camera and positive kinematics Cartesian coordinates of the double robots are synchronously collected, a calibration result is obtained through optimization of a least square method by adopting a hand-eye calibration algorithm, and the effectiveness of the calibration result is judged through the average value of data calibration precision until calibration of the double robots is completed. Simulation modeling, collision detection and a hand-eye calibration technology are fused, a complex calibration problem is converted into a virtual environment parameter optimization process through a self-adaptive sampling strategy and a data synchronous acquisition mechanism, calibration robustness and precision are remarkably improved, and guarantee is provided for high-precision cooperative control of double robots.

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.

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 provides a robot calibration method based on a feature differentiation learning neural network model. According to the method, a robot operation reference object is calibrated through a credible feature discrimination convolutional neural network, a feature differentiation learning strategy and a three-dimensional frame prediction network based on a view cone-link dynamic graph. According to the invention, in combination with multi-modal visual information data, a credible feature discrimination convolutional neural network, a feature differentiation learning strategy and a three-dimensional frame prediction network based on a view cone-link dynamic graph are constructed, so that the problem that an existing robot calibration method is easily influenced by polymorphic reference substances and random noise is solved; the robot calibration precision in a large-scale production environment is improved.

The invention discloses an inspection positioning method, device and equipment for an inspection robot of a belt conveyor, relates to the technical field of inspection of belt conveyors, and can solve the technical problem that an existing rail-mounted robot is large in error in high-precision inspection positioning. Comprising the following steps: acquiring image video data of environment and equipment, acquiring initial parameter information of an inspection point according to the image video data, and drawing an inspection environment map model according to the image video data and the initial parameter information of the inspection point based on calibration of the initial parameter information of the inspection point; installing a track system according to the inspection environment map model, setting an inspection mode, and mounting and operating an inspection robot on the track system based on the inspection mode; and calibrating the track mileage to obtain the calibrated track mileage, and positioning the inspection robot to the position of the robot by using the positioning tag reader and the multi-circle absolute value encoder based on the calibrated track mileage so as to monitor whether the equipment to be inspected has a fault or not.

The invention discloses a robot calibration method for spine endoscopic surgery, which comprises the following steps: S1, optical marking points are pasted on the skin or bony structure of a patient, the skin marking is used for fixing a reflective ball by using a medical adhesive tape, the bony marking is percutaneously implanted into a spinous process or crista iliaca through a titanium alloy bone nail, and at least six marking points are needed. According to the method, minimally invasive property and stability are both considered through a double marking strategy, six points cover three vertebral bodies to ensure the integrity of an anatomical range, registration errors caused by breathing / body position changes are reduced, meanwhile, non-rigid registration is combined with a B spline grid (10 mm) to consider calculation efficiency and spine physiological curvature adaptability, high-precision surface reconstruction is achieved through a Marching Cubes algorithm, and the method has the advantages of being high in precision and high in precision. An error suppression mechanism is formed by + / -0.25 mm precision and redundancy measurement (five times of sampling) of the optical tracking system, registration robustness is improved through SVD and ICP double-algorithm complementation, multi-constraint path planning is achieved through an A * algorithm and Monte Carlo simulation, and a 4 mm safety corridor provides a buffer space for instrument errors.

A system includes a chamber, a robot within the chamber, the robot including a plurality of links. The system further includes a vertically oriented sensor within the chamber, the vertically oriented sensor to detect a presence of one or more of the plurality of links. The system further includes a controller, to perform for each link to cause the robot to move the link through a field of view of the vertically oriented sensor. The controller further determines a zero horizontal position for the link based on the position of the link at which the link was detected by the vertically oriented sensor. The controller further automatically calibrates the robot within the chamber based on the zero horizontal position determined for each of the plurality of links.

A method of calibrating a robotic arm which includes perform iterative eye-in-hand and robot calibration, using a calibrated end of arm camera with known intrinsic parameters and a static target, to obtain eye-in-hand transformations and robotic parameters. The method further uses robotic parameters to estimate pose of end of arm, for eye-to-hand calibration, to obtain eye-to-hand transformations and calculates final error compensation based on the robotic parameters, eye-to-hand transformations, and eye-in-hand transformations. In one embodiment, the method calculates a robot positioning error map function, the robot positioning error map function used to adjust movement parameters for the robotic arm.

The invention relates to the field of robot calibration, in particular to a robot end tool calibration method, device and equipment and a computer readable storage medium. The method comprises the steps that whether a preset calibration assembly and a to-be-calibrated laser range finder meet the requirement that the calibration assembly is connected with the laser range finder or not is determined, and the position of a light spot formed on the calibration assembly by laser emitted by the laser range finder is located in a target area of the calibration assembly; if yes, when the calibration assembly is located at all the target positions, the target robot is controlled to complete contact between the target area and the preset fixed position in multiple different poses; and calibrating the relative position relationship between the laser range finder and the tail end of the robot according to the pose coordinates of the tail end of the robot and the ranging value output by the laser range finder when the calibration assembly is located at the target position and the target robot is located at each pose. The accuracy and efficiency of calibration of the relative position of the laser range finder at the tail end of the robot and the tail end of the robot can be improved.

The invention discloses a robot kinematics parameter error calibration method based on subspace measurement, and the method comprises the steps: setting a measurement system, dividing the measurement system into a plurality of subspaces according to the working space of a robot, and placing standard part units in different subspaces; a monocular cross-structured light measurement unit fixed at the tail end of the robot is used for respectively measuring standard component units in each delimited subspace, an objective function is established, and an algorithm is used for iterating the objective function, so that the purpose of robot calibration is achieved. According to the invention, the problem of light shielding during measurement of the laser tracker is avoided. The problems that the calibration of the whole large space of the robot needs large workload and long time, the calibration precision of the large space is usually not high, and the specific small space cannot meet the calibration of the working space of the robot are solved. Meanwhile, according to the working requirements of different subspaces of the robot, independent calibration of the subareas is carried out, so that the robot meets the positioning precision requirements of different subspaces in different working modes.

The invention discloses a robot hand-eye automatic calibration method, which comprises the following steps of S100, mounting a calibration plate on a flange plate at the tail end of a robot, and enabling the center O of a coding area of the calibration plate to be collinear with a six-axis rotating shaft of the robot; s200, determining the distance d between the center of the flange plate and the center O of the coding region of the calibration plate, and the size of the coding region: the length l and the width w; s300, taking d as Z data of current tool data calibrated by the robot; s400, determining a camera view field area needing to be calibrated, and setting three image acquisition plane areas: an upper layer area TopArea, a middle area MidArea and a bottom layer area BotArea; according to the full-automatic hand-eye calibration method for the eyes outside the hands, manual participation is reduced or completely avoided through an automatic means, the calibration efficiency can be remarkably improved, and the consistency and high precision of the calibration process can be guaranteed.

A method for calibrating a robot is disclosed. A working space of the robot at least partly overlaps with a working space of a machining and / or production tool. The robot is moved such that a reference point of the robot is at a first position within the working space of the machining and / or production tool. A first position value for the robot at the first position is compared with a first position value for the machining and / or production tool at the position. If the first position value for the robot differs from the first position value for the machining and / or production tool, the first position value for the robot is corrected or the first position value for the machining and / or production tool is corrected such that the first position value for the robot and the first position value for the machining and / or production tool are the same.

The invention relates to a machine tool and robot cooperative machining method for large thin-walled cylinder components, which is characterized by comprising the following steps of: 1, establishing hardware configuration of a system; 2, calibrating the system; 3, on the basis of the matrix transformation relation, the relative pose # imgabs0 # in the component coordinate system {PF} and the robot coordinate system {BF} is obtained through calculation and solution by adopting a formula; and 4, after a calibration result is obtained, the component is milled. Therefore, the positioning precision of offline programming of the robot can be improved by means of the precision of the machine tool, and the machining efficiency is improved. In addition, the position relation between the robot and the component is calibrated through the machine tool, and limitation during robot calibration is avoided.

The invention discloses a new energy automobile automatic test method and system, and relates to the technical field of electric automobile detection. A vehicle is fixed to a rotating hub platform, bus connection and robot calibration are completed, a digital twin model is constructed, and initial parameters are configured; decomposing a working condition curve to extract core parameters, and generating a refined control logic table in combination with the virtual model; the lower computer cooperates with the robot and the rotating hub platform to execute test operation according to a protocol; optimal control parameters are fed back based on real-time data and the virtual model; synchronously acquiring various parameters of the vehicle, the robot and the rotating hub; fusing the data and performing simulation comparison to generate a comprehensive test report; adjusting parameters and repeating the test to form a complete closed loop. Through multi-device cooperation, dynamic adaptation and data fusion, the test precision and stability are improved, the vehicle type adaptation capability is enhanced, the scene coverage range is expanded, the test safety is guaranteed, the test efficiency is improved, function extension and flexible operation and maintenance are supported, and the diversified test requirements of the new energy vehicle are met.

The application provides a guided tooth repair method, system and storage medium, which realizes the conversion and unification of the coordinate systems among multiple systems through technical steps such as CBCT data acquisition, CT three-dimensional model creation, robot calibration, matrix conversion relationship analysis, and the like, and then, after a tooth repair scheme is formulated based on the CT three-dimensional model, the matrix conversion relationship among the coordinate systems of the oral cavity reference plate, the CT and the optical positioner is obtained, the cutting tool and the repair tool on the robot are guided through the optical positioner, the real-time pose of the patient is judged in the assistance of the optical positioner by combining the running track data of the cutting tool and the running track data of the repair tool, the cutting and repair are guided in real time, human errors are avoided, the operation precision is improved, and the tooth repair effect is ensured.

The present application relates to the field of robot calibration, and discloses a surgical robot calibration method and device, a surgical robot and a storage medium, the method comprising: controlling the surgical robot to move according to a preset calibration route, so that the surgical robot reaches each calibration pose in turn; the calibration poses include an initial pose, a first translation pose, a second translation pose and at least two rotation poses; a camera device is used to capture a marker point on the surgical robot, and pose data of the surgical robot at each calibration pose is recorded; a first rotation matrix from a base coordinate system to a camera coordinate system is calculated according to the initial pose, the first translation pose and the second translation pose; a first translation matrix from the base coordinate system to the camera coordinate system, a second rotation matrix and a second translation matrix from a flange coordinate system of the surgical robot to a reference coordinate system of the surgical robot are calculated according to the first rotation matrix and the at least two rotation poses.

The application relates to the technical field of robot calibration, in particular to a robot body parameter self-calibration method based on a ball center distance constraint, which comprises the following steps: a calibration error model based on a ball center distance constraint is established; a calibration equation of robot body parameter error and distance error is obtained; a constraint ball plate used for calibration is designed to obtain measurement data and establish a constraint equation; an LM algorithm is used for parameter identification of the constraint equation to obtain a robot body parameter compensation value; and the robot body parameter compensation value is compensated to a robot kinematics model for simulation verification. The method can realize simple and efficient calibration of the robot body parameter by means of a self-made calibration ball plate, does not need to rely on external high-price measuring equipment, and can achieve the purpose of improving the absolute positioning accuracy of the robot.

The present invention discloses an automated inspection system for computer room operation and maintenance management, which relates to the technical field of computer room operation and maintenance management. The system comprises a route acquisition module, a rated control steering angle acquisition module, a benchmark route acquisition module, an inspection robot calibration line acquisition module, a deviation angle acquisition module, a required adjustment angle acquisition module and an update module. By using the required adjustment angle corresponding to each intermediate control node as the new rated control steering angle value corresponding to each intermediate control node, the rated control steering angle value corresponding to each intermediate control node is adjusted and updated, so that the robot can subsequently operate according to the corrected parameters when turning at the node, so that the robot can turn according to the corrected angle when passing the same node subsequently, so that the robot can turn more accurately on the predetermined inspection route, thereby significantly improving the inspection accuracy and ensuring accurate monitoring of the computer room equipment status and environmental data.

The invention discloses a robot calibration point selection method and system and a storage medium. The robot calibration point selection method comprises the following steps: acquiring an initial point position set; according to a calibration requirement set by a user, determining weights of the plurality of evaluation elements, and performing weighted calculation on the plurality of evaluation elements based on the weights to obtain a weighted evaluation index; screening out a target calibration point set from the initial point position set based on the weighted evaluation index; and utilizing the target calibration point set to calibrate kinematics parameters of the robot. Through a strategy of combining a weighted comprehensive evaluation index and an intelligent point selection algorithm, the problems that selection of a single evaluation index is not comprehensive, an existing point selection method is easily influenced by gross errors, and the stability of calibration precision in space is insufficient are solved.

The present invention discloses a robot calibration method for LM and ARO algorithms, comprising step S1, establishing a robot kinematic error model using an MDH model; step S2, obtaining robot joint data and laser tracker measurement data of sampling points; step S3, calculating the distance values ​​between two points corresponding to the robot end points, and establishing an objective function through the distance difference between the two points; step S4: performing parameter iterative optimization on the objective function of step S3 using the LM‑ARO algorithm to obtain a robot kinematic parameter error value that satisfies the minimum objective function value. The present invention solves the rounding error of high-order terms of the single LM algorithm, and also overcomes the problem of slow search speed and low efficiency caused by the large search range of the single ARO algorithm. No constraints of standard parts are required. At the same time, the calibration cost is low, and the robot kinematic parameter error can be effectively calibrated, significantly improving the accuracy level of the robot.

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.

The application discloses a robot calibration point selection method and system and a storage medium. The robot calibration point selection method comprises the following steps: acquiring an initial point set; determining the weights of a plurality of evaluation elements according to a calibration requirement set by a user, and performing weighted calculation on the plurality of evaluation elements based on the weights to obtain a weighted evaluation index; screening a target calibration point set from the initial point set based on the weighted evaluation index; and calibrating the kinematic parameters of a robot by using the target calibration point set. Through a strategy combining a weighted comprehensive evaluation index and an intelligent point selection algorithm, the problems of incomplete selection of a single evaluation index, influence of an existing point selection method on a gross error and insufficient stability of calibration accuracy in space are solved.

The utility model discloses a workbench for calibration of an ASR artificial intelligence storage robot. The workbench comprises a workbench base; a slope plate is installed on one side of the workbench base and used for an ASR robot to climb to the top of the workbench base. According to the working table of the ASR robot, the slope plate is in butt joint with the working table base, the ASR robot can be conveniently and rapidly transferred to the top of the working table base, then the middle wheel positioning wheel is used for positioning the positioning middle wheel, and therefore the working table of the ASR robot is convenient to use. The front moving wheels and the rear moving wheels are ensured to be located at the top of the four-wheel reference table, then the ASR robot is transversely adjusted through the side positioning adjusting rod, it is ensured that the ASR robot is located at the center of the top of the workbench base, the two-dimensional code on the ground code plate is conveniently shot by the ground code camera, and the first detection reference surface and the second detection reference surface are matched. The radar detection rods at the front position and the rear position are used for rapid detection, and efficient and rapid factory detection and calibration are achieved.

The application provides a robot calibration method based on a feature difference learning neural network model, which calibrates a robot work reference object through a trusted feature discrimination convolutional neural network, a feature difference learning strategy and a three-dimensional bounding box prediction network based on a view cone-link dynamic graph. The application combines multi-modal visual information data to construct a trusted feature discrimination convolutional neural network, a feature difference learning strategy and a three-dimensional bounding box prediction network based on a view cone-link dynamic graph, solves the problem that existing robot calibration methods are easily affected by multi-form reference objects and random noise, and improves the robot calibration precision in a large-scale production environment.

The present invention discloses a robot calibration method based on position and distance constraints, including establishing a robot kinematic model and a kinematic error model based on position and distance constraints; installing an end calibration device to the end of the robot, and installing a geometric constraint device in the robot's workspace; dragging the robot so that the calibration ball of the end calibration device is constrained to each ball seat on the geometric constraint device, and each ball seat touches several times in different configurations, reading and recording the joint angle data measured each time; identifying the corresponding robot kinematic model parameters; and compensating the kinematic model parameter errors obtained by identification to the robot controller. The present invention has the advantages of low cost, good portability, simple operation, and not easy to damage.