64 results about "Quaternion" patented technology

This invention addresses the common failure problems encountered by actuators during the flight of heavy-lift launch vehicles in disturbed environments. It studies a method for achieving rocket attitude stabilization and tracking under complex conditions, proposing an adaptive fault-tolerant backstepping attitude control design method. First, to avoid attitude singularities, a quaternion-based kinematic and dynamic model of the launch vehicle oriented towards actuator failures is established. Based on this model, an adaptive fault-tolerant backstepping attitude controller is designed to adaptively estimate and compensate for uncertainties and external disturbances, handling potential failures and ensuring the stability of the control system. The algorithm proposed in this invention is more effective and superior than traditional adaptive backstepping methods.

The application provides a unit quaternion-based error compensation calibration method, comprising the following steps: S11, establishing a calibration measurement system; S12, CCD camera calibration; S13, initial light plane calibration; S14, angle correlation establishment; S15, initial rotating shaft linear equation calibration; S16, assembly error compensation and rotating shaft optimization; and S17, dynamic light plane calibration. The application directly takes the rotating shaft of the motor of the galvanometer as a reference, calibrates the origin of the galvanometer linear laser three-dimensional measurement system on the rotating shaft of the motor of the galvanometer, does not need to add an additional coordinate system, reduces the conversion error of the coordinate system, does not need an additional work platform, can not consider the assembly error of the target plane and the workbench, and the calibration based on the unit quaternion can effectively reduce the complexity of the mathematical model and improve the calibration efficiency.

The application discloses an anti-unwinding flexible spacecraft attitude tracking composite control method, first, based on the quaternion method, a flexible spacecraft attitude tracking error kinematics and dynamics model is established; then, the flexible accessory vibration mode, external environmental disturbance and model uncertainty are regarded as a lumped disturbance, a generalized proportional integral observer is designed, and the lumped disturbance is observed and estimated; finally, a non-singular terminal sliding mode surface is constructed, the lumped disturbance observation and estimation compensation of the generalized proportional integral observer is taken as a feedforward signal, and a feedforward-feedback anti-unwinding attitude tracking composite controller is designed. Through determining appropriate control gain, the closed-loop attitude tracking error system is globally finite time stable, and the anti-unwinding effect can be realized. The application can realize finite time attitude tracking of the flexible spacecraft, has high attitude tracking precision and strong robustness.

The application discloses a kind of asymmetric configuration satellite attitude maneuvering process coupling compensation method, comprising: establishing the satellite attitude dynamics model including the non-diagonal item of moment of inertia matrix;Read current attitude sensor data, and calculate deviation quaternion and deviation angular velocity;According to the attitude dynamics model and current angular velocity data, calculate coupling compensation feedforward control torque;Based on the coupling compensation feedforward control torque, deviation quaternion and deviation angular velocity, the control torque after compensation is calculated;The control torque after compensation is limited and priority torque distribution, and the final control torque is obtained;Final control torque is sent to actuator drive satellite and carries out attitude maneuvering.Solve the problem that coupling effect caused by inertia product cannot be effectively compensated when asymmetric configuration satellite is in large-angle attitude maneuvering in prior art, and then affect control precision and stability.

The application discloses a kind of unmanned plane freedom degree attitude test analysis system and method, wherein a kind of unmanned plane freedom degree attitude test analysis system, freedom degree attitude simulation module, based on quaternion dynamics model, simulates the attitude change of unmanned plane;Sensor dynamic calibration module, automatically identifies and calibrates gyroscope zero offset, accelerometer scale error, magnetic compass hard iron / soft iron interference;Multi-throttle vector control module, respectively control motor throttle, simulate extreme working condition;Flight control algorithm verification module, real-time injection attitude error, assess convergence time, overshoot, steady-state error;Data fusion and visualization module, real-time fusion data, support multi-dimensional visualization;Automated test script module, support Excel process driven test;Authority and data security module, carry out hierarchical authority management, support test data encryption, operation log audit, parameter tamper prevention.

The present disclosure provides a physical information neural network-based pose estimation method, device and equipment, relating to the technical field of computer, the method comprising: collecting an original sensor sequence and preprocessing the original sensor sequence to obtain a time-frequency representation; determining a multi-scale feature and a residual attention weight based on the time-frequency representation; inputting the multi-scale feature and the residual attention weight into a physical information neural network model to obtain an angular velocity estimation and a pose quaternion update term; calculating a physical residual loss according to the angular velocity estimation and the pose quaternion update term and a physical kinematics constraint, and constructing a total loss function based on the physical residual loss and a measurement consistency loss; optimizing network parameters of the physical information neural network model based on the total loss function to obtain a trained pose estimation model; compressing and deploying the pose estimation model, and generating a pose estimation result based on real-time collected sensor data through the pose estimation model. Low-cost and high-precision pose estimation can be achieved.

The application discloses a four-element-based three-dimensional human body posture estimation motion correction method, which comprises the following steps: 1, collecting motion data and performing data preprocessing; 2, using a convolutional neural network to extract human body joint features; 3, using the extracted joint features to construct a quaternion for rotation; 4, using three-dimensional coordinate values and a method for calculating angles in a three-dimensional space to calculate the angles between each joint and the skeleton, which are used for posture correction; and simultaneously, the speed is corrected by calculating the slope. The application improves the accuracy of posture correction in a three-dimensional space through quaternion rotation; the determination method of the motion speed in the three-dimensional space is redefined through the Euclidean distance and the speed of angle change; and the application can achieve good effects in the determination of motion speed and action recognition in the three-dimensional human body posture estimation in sports health.

This invention relates to a method and system for optimizing coating trajectory to ensure uniformity of spacecraft coating thickness. The method includes: acquiring a model of the surface to be coated, generating a regular grid initial coating curve and setting constraint parameters; mapping the curve to a complex surface using a pseudo-projection algorithm, and generating a fully covered, non-intersecting initial trajectory after trajectory correction; based on an experimentally calibrated coating deposition model, constructing a multi-objective optimization function that minimizes coating thickness deviation while considering trajectory smoothness and operation time, using trajectory waypoint coordinates, coating gun attitude quaternions, and coating segment duration as optimization variables, and applying constraints such as coating distance, velocity, and attitude; using an interior-point solver for iterative optimization, limiting variable iteration deviations to ensure model accuracy; and outputting an directly executable optimized trajectory. This invention can automatically adapt to the coating requirements of complex surfaces, significantly improve coating thickness uniformity, control deviations within the allowable range of aerospace processes, and effectively improve operational accuracy and efficiency.

This invention discloses a data glove for a teleoperation system and its control method. The data glove body is worn on the user's hand, and a signal transmission network is constructed between hand, wrist, and arm data units mounted on the glove body. Complete kinematic chain data from the shoulder joint to the finger joints is collected by each data unit and transmitted through the signal transmission network, including quaternion pose data and gesture data. The quaternion pose data is processed to obtain a spatial pose matrix, and the gesture data is processed using a gesture mapping algorithm to obtain a gesture sequence number. A master-slave mapping algorithm maps the workspace of the glove to the workspace of the slave device, thereby enabling the master device to freely control the slave robotic arm and execute specific complex task processes. This invention, through modular sensor layout and algorithm optimization, achieves precise, intuitive, and natural control of the slave robotic arm by the operator, reducing operational complexity and improving the user experience.

This invention relates to an attitude calculation method for an unmanned aerial vehicle (UAV) attitude reference system, belonging to the field of UAV navigation. In this invention, the collected sensor data is first filtered to obtain an initial unit quaternion from the navigation coordinate system to the vehicle coordinate system. The accelerometer output is normalized and an error vector is constructed with the normalized gravity vector. The vehicle motion mode is determined by the accelerometer and gyroscope outputs, and the gain coefficient is adaptively adjusted to calculate the gyroscope error correction, thus completing the attitude update and correcting the horizontal attitude. Simultaneously, the magnetometer output is evaluated; if the magnetometer output is valid, the heading angle is corrected, and the corrected three-axis attitude angles are output in real time. This invention uses only quaternions for calculation, avoiding the calculation of rotation matrices and improving calculation efficiency. Compared to traditional complementary filtering algorithms, it incorporates vehicle motion mode judgment and adaptive complementary filter parameter adjustment, avoiding erroneous attitude corrections by the accelerometer under high dynamic conditions. By applying a second-order complementary filter to process accelerometer and magnetometer data for attitude compensation, horizontal attitude correction can be avoided when magnetometer data is unavailable, achieving decoupling of attitude correction.

The present disclosure provides a pedestrian integrated navigation method based on a multi-error factor tight coupling model, which uses a sensor arranged on the chest to collect inertial measurement data; an INS performs inertial navigation calculation based on the inertial measurement data, and updates the INS position; an iterative principal component analysis method is used to determine the angle error between the heading and the walking direction under multi-gait conditions, to compensate for the MetCM heading based on quaternion calculation, and to obtain the updated and compensated MetCM position; a Kalman filter combining the MetCM model and the INS error model is constructed to estimate the position error, to compensate for the INS position and the MetCM position, and to output the calibrated position. The present disclosure can effectively improve the positioning accuracy of autonomous navigation.

The application discloses an industrial intelligent agent system and method fusing digital twin and a four-element core, belongs to the field of artificial intelligence, and comprises a digital twin perception layer, a four-element fusion core layer, a hybrid reasoning engine and an interpretable report generator.The digital twin perception layer is used for acquiring real-time state data of a physical entity; the four-element fusion core layer integrates OWL ontology modeling, graph database storage, large language model interaction and multi-physical field agent model, and generates a four-element collaborative knowledge processing result; the hybrid reasoning engine performs parallel rule reasoning, graph algorithm mining, large language model reasoning and agent model reasoning and fuses to generate a comprehensive reasoning conclusion; and the interpretable report generator generates a multi-modal report containing a reasoning path and physical evidence.The application realizes interpretable tracing of a decision-making process through four-element collaboration, realizes millisecond-level physical quantity prediction through an agent model, realizes continuous evolution of knowledge through a dynamic evolution module, and significantly improves the reliability, real-time performance and adaptability of an industrial intelligent system.

The application relates to the technical field of coal mine safety monitoring, and discloses a multi-source heterogeneous ground disaster monitoring data fusion and space-time correlation analysis method and system for a coal mine power supply line, which comprises the following steps: collecting multi-source ground disaster data of the coal mine power supply line, and performing standardization processing on the multi-source ground disaster data to obtain a standardized multi-source heterogeneous data set; sequentially performing feature-level fusion and decision-level fusion on the standardized multi-source heterogeneous data set to obtain a real value domain global ground disaster feature tensor; analyzing the global ground disaster feature tensor by using a coal mine ground disaster space-time correlation analysis model constructed based on a quaternion algebra structure, outputting ground disaster prediction results of multiple regions of the coal mine power supply line, and performing ground disaster risk grading early warning based on the ground disaster prediction results, wherein the ground disaster prediction results comprise a ground disaster occurrence probability and a ground surface deformation amount prediction result. The accuracy of ground disaster identification and the advance nature of early warning of the coal mine power supply line are significantly improved.

The present application relates to the field of aerospace technology, in particular to a kind of low-orbit flexible satellite attitude stabilization control method with SADA device, comprising: using attitude quaternion to satellite attitude kinematics dynamics modeling;Desired quaternion is used to error attitude kinematics dynamics modeling;S3. the method for adopting classic feedback control combined with nonlinear compensation control, error attitude kinematics dynamics equation design obtains attitude controller;Real-time acquisition satellite rotational inertia parameters, and based on the relationship between the attitude controller control parameter and satellite rotational inertia parameters design attitude controller control parameter;Real-time satellite rotational inertia is obtained, and the parameter of attitude controller in step S4 is updated using real-time calculated satellite rotational inertia parameter.The present application uses the way of mathematical analysis calculation, according to the rotation of SADA, the current satellite rotational inertia is calculated in real time, and is used to update the parameter of attitude controller, and the global stability of attitude control is guaranteed.

The present application relates to a kind of attitude prediction formula star tracking method, it is related to star sensor technical field.The method includes the following steps: obtaining historical angular velocity data;Predict the next frame angular velocity;Predict the next frame attitude quaternion;Project the sky area star to image plane;Window matching is carried out between projected star and the next frame observation star;Calculate the next frame accurate attitude quaternion;The target of window matching success is used for attitude solution, obtain the next frame accurate attitude;Repeat the above steps, realize autonomous star tracking.The attitude prediction formula star tracking method of the present application, by polynomial fitting historical angular velocity data, can quickly and accurately predict the next frame angular velocity, significantly improve real-time and accuracy;Can well adapt to large angular velocity maneuver, enhance the tracking ability of star sensor in complex dynamic environment;Reduce the dependence on external sensor, improve the independence and anti-interference ability of system, while simplifying the calculation process, improve overall computing efficiency.

The application discloses a soft robot shape perception method, device, equipment and computer storage medium, relates to the shape perception technical field, and discloses a soft robot shape perception method, comprising: acquiring sensor collection data, wherein the sensor collection data includes acceleration, angular velocity and node length change value of the soft robot node;According to the acceleration, angular velocity and preset Kalman filter algorithm, the compensation attitude quaternion is determined, and the compensation attitude quaternion, the acceleration and the node length change value are trained in the preset neural network model, and the target neural network model is obtained;According to the target neural network model, the shape of the soft robot is perceived.The application improves the accuracy of soft robot shape perception.

This invention relates to the field of unmanned aerial vehicle (UAV) control technology and includes the following steps: S1, establishing a discrete nonlinear dynamic model with disturbances based on quaternions; S2, designing a lightweight nonlinear model predictive controller based on real-time iteration of sequential quadratic programming; S3, constructing a lightweight MLP disturbance observer to achieve real-time estimation of six-dimensional disturbances; and S4, designing a position-torque dual-layer feedforward compensation strategy. This invention significantly reduces the online computation of NMPC by combining the SQP_RTI real-time iterative framework with a hot-start and matrix pre-storage mechanism, enabling millisecond-level real-time operation on the airborne platform. It employs a 26-dimensional feature fusion MLP network to achieve joint estimation of disturbance forces and torques, eliminating dependence on precise model parameters. The dual-layer separate feedforward design, which corrects the reference trajectory at the position layer and directly compensates for motor speed at the torque layer, avoids coupling interference from a single compensation method, achieving high-precision trajectory tracking even under external disturbances such as wind fields and sudden load changes.

This application discloses a motion data redirection method, system, device, and storage medium. The method includes the following steps: acquiring the first skeleton coordinates of the target character, the second skeleton coordinates of the original character, the first driving quaternion of the original character in the current frame, the first root node coordinate information of the original character in the current frame, the first whole-body node coordinate information of the target character in the previous frame, and the fourth whole-body node coordinate information of the original character in the previous frame; determining the temporary second whole-body node coordinate information of the target character in the current frame; determining the third whole-body node coordinate information of the original character in the current frame; determining the node identifier with the smallest coordinate change; determining the motion change of the node corresponding to the node identifier in the target character; and adjusting the first whole-body node coordinate information of the target character in the current frame. This method can be applied to both real-time and non-real-time motion data redirection, and has strong practicality and scalability. This application can be widely used in the field of inertial motion capture technology.

The application relates to a time-optimal three-axis reorientation method and device for an inertia-symmetrical rigid spacecraft, which determines an angular velocity analytical expression according to inertia symmetry of the spacecraft and a time-optimal control switch structure set in advance; through introduction of a new inertia axis coordinate system, the symmetry characteristic of a reorientation track is explicitly derived; a Radau pseudo-spectrum discrete method is used to discretize a quaternion dynamic equation, so that the time-optimal reorientation problem is converted into a nonlinear programming problem; through given two parameter values, the discretized quaternion dynamic equation is converted into a linear equation set and is solved, a discrete quaternion value sequence obtained through decomposition is used, a gradient method or a Newton method is used to optimize the two parameters, and a time-optimal reorientation track is determined according to an optimization result. The method does not need to perform numerical integration or solve a large-scale nonlinear programming problem, and the calculation efficiency is significantly improved, so that fast and accurate track generation of an inertial rigid spacecraft is realized.

This invention relates to an adaptive control method and system for maintenance unmanned aerial vehicles (UAVs) considering the complex electromagnetic environment of rooftops. The method includes: acquiring spatial magnetic field gradient distribution data; performing recursive least-squares adaptive compensation on the original IMU angular velocity to generate a corrected angular velocity; decoupling the attitude calculation deviation introduced by electromagnetic interference based on the corrected angular velocity and IMU acceleration; fusing GNSS positioning data to generate flight state parameters; extracting features from binocular visual images and millimeter-wave radar point clouds respectively and constructing multi-source confidence weighting factors, performing deep fusion to generate a fused depth map; back-projecting the fused depth map into a local three-dimensional point cloud and identifying obstacles; constructing an inertial adaptive braking distance model based on the current speed and payload mass to generate an obstacle spatial distribution map; planning a smooth obstacle avoidance path with the map and current position as constraints; inputting the compensated attitude quaternion into the model reference adaptive controller to counteract electromagnetic residual torque disturbances and generating motor control commands.

The application relates to an inertial navigation comprehensive correction method based on a normal vector position model, which comprises the following steps: receiving a real-time rotation angular velocity vector and a specific force vector, binding initial navigation parameters, obtaining an initial normal vector position vector, an initial quaternion position vector and an initial direction cosine matrix, obtaining an initial velocity and an initial attitude matrix; obtaining a current velocity, a current attitude matrix and a current quaternion position vector; obtaining a current damping velocity and a current damping quaternion position vector, calculating a normal vector integral term; judging whether comprehensive correction is needed, if yes, adjusting an external reference position based on an observation number; if the observation number is greater than 1, adjusting a horizontal position to the external reference position, obtaining a drift angle and an azimuth gyro drift, correcting an attitude matrix output according to the drift angle, and using the azimuth gyro drift for navigation calculation; recording a time of successful observation and setting the normal vector integral term to zero; repeating the foregoing steps until navigation is completed.

The application provides an industrial defect detection and cause analysis method, device, equipment and storage medium, and relates to the technical field of industrial component manufacturing. The method comprises the following steps: selecting a suitable visual language large model as a basic model; introducing a modal fusion module to efficiently fine-tune the model, the module fuses visual and text information by using cross attention and a neural network based on quaternion operation, so as to enhance the attention of the model to the defect area and the information utilization efficiency, and obtain a model with basic defect positioning and cause analysis capability; and collecting actual production line data to continuously incrementally learn the model, so that the model is adapted to a specific production environment and maintains the detection capability for new and original products. The application realizes integrated output of defect positioning and cause analysis, and improves the automation and intelligent level of industrial quality inspection.

The present invention discloses a high-efficiency and stable method for simulating inextensible ropes in crane and hoist. The piecewise linear inextensible rope is usually represented by the Cartesian coordinates of the vertices and the quaternions on the segments, which uses too many degrees of freedom and needs many constraints, bringing unnecessary numerical difficulties and computational burden to the simulation. The present invention proposes a compact representation which uses the minimum number of degrees of freedom and naturally satisfies all the additional constraints. Specifically, the rope is regarded as a chain of rigid segments, and its shape is encoded as the Cartesian coordinates of its root vertex and the axis-angle representation of the local coordinate system on each segment. Under the representation of the present invention, the implicit time-stepping matrix has a special non-zero pattern. Using the non-zero pattern, the present invention designs a preconditioner which can solve the related linear equations with approximate linear complexity, and its speed is improved by one to two orders of magnitude compared with the widely used block-diagonal linear PCG solver.

The present application relates to a kind of point cloud processing and path planning method for automatic marking of workpiece, belong to workpiece automation processing technical field, to solve the problem of low efficiency, poor precision and existing system insufficient adaptability of artificial marking.The technical scheme includes: the three-dimensional model of workpiece is converted into point cloud, and the main plane is extracted by random sampling consistency algorithm;Adopt spatial index clustering optimization boundary;Based on principal component analysis, construct local coordinate system;Generate the minimum circumscribed rectangle boundary;Calculate the rotation quaternion posture and sample trajectory point;Define workpiece coordinate system to realize space transformation;Output standardized trajectory file.The method significantly improves the adaptability of complex surface, realizes high-precision trajectory automatic generation, reduces the dependence on artificial experience, and the standardized interface is convenient for integration robot system, promotes the intelligent upgrading of industrial marking process.

This invention discloses a virtual simulation method and system for marine radar, comprising the following steps: constructing a virtual test environment consistent with the real marine environment, including an unmanned vessel, marine radar, and maritime targets; using a quaternion calculation method to transform measurements in the local coordinate system of the virtual radar to the world coordinate system; determining the radar field of view through horizontal and vertical scanning coverage; realizing simulated ray tracing and collision detection of the marine radar beam; calculating echo distance and angle, calculating echo intensity, and generating standardized radar echo data records; dynamically adjusting the echo intensity through adjustable gain control and range compensation mechanisms, and mapping the echo data to a color space; persistently storing and time-attenuating the echo data to simulate radar afterglow effects; and drawing range rings, azimuth markers, and dynamic scan lines on the radar display interface to construct a complete radar visualization system.

This invention relates to the field of marine geological 3D visualization technology, specifically disclosing a marine geological VR 3D visualization simulation system that integrates panoramic real-world footage. The system includes a visualization simulation platform, which is communicatively connected to the following modules: a coordinate mapping and alignment module, used to precisely align the spherical UV coordinates of the panoramic real-world footage with the terrain world coordinate system in Unity3D through inverse projection transformation using a unified virtual-real coordinate mapping algorithm, and to smooth the parallax jumps during head rotation using quaternion interpolation. This invention precisely aligns the spherical UV coordinates of the panoramic real-world image with the 3D terrain world coordinate system using a unified virtual-real coordinate mapping algorithm, and uses quaternion spherical linear interpolation to smoothly transition the parallax changes during head rotation, eliminating the visual disconnect between the panoramic background and the 3D terrain, and ensuring the continuity and stability of spatial perception when the user's perspective changes.

The application relates to the field of three-dimensional target recognition, in particular to a method and equipment for detecting the rotational similarity of target objects based on spatial postures. The method comprises the following steps: extracting quaternions from two target objects to be detected respectively to obtain a first quaternion and a second quaternion; performing primary detection, standardized comparison, flip detection, Lie group manifold geodesic line gradient optimization detection and symmetry combination enumeration detection according to the angle difference between the first quaternion and the second quaternion; if the result of any one of the above detections is matching, subsequent detection is not performed, and it is directly determined that the two target objects to be detected are rotational similar objects. In this way, the posture misjudgment problem of symmetrical objects in the prior art can be solved, and the robustness of rotational posture comparison is greatly improved.

This invention relates to the field of computer vision technology, specifically disclosing a robust point cloud registration method and system based on block-aware serialization spatial learning. Addressing the problems of high computational complexity, noise sensitivity, and poor registration performance in partially overlapping scenes, existing methods employ a point cloud registration network comprising a segmentation and serialization module, a backbone network (encoder-decoder structure), and a dual-dominating head. The segmentation and serialization module divides the point cloud into multiple independent blocks and serializes them to maintain spatial locality; the encoder extracts multi-scale block-level features layer by layer; the decoder further aggregates contextual information; and the dual-dominating head predicts rotation quaternions and translation vectors respectively. Experiments show that this invention outperforms traditional iterative methods and existing deep learning models in registration accuracy, maintains stable performance in noisy environments and low-overlap scenes, and possesses high inference efficiency and low memory usage.

The application relates to a multi-head fusion star sensor system use method, and relates to the technical field of satellite attitude measurement and determination. Three star sensor probes are arranged on a satellite, and each star sensor is provided with a matrix; four groups of attitude quaternions output by the star sensor correspond to three probes and fusion star sensors respectively; a reference probe is selected to set a mark, and the attitude reference of the attitude quaternions output by the fusion star sensor is adjusted to be consistent with the matrix of the probe; the angles between the three probes and stray light including sunlight and earth light are calculated in real time; the effectiveness flags of the three probes are judged to be effective or ineffective; if the three probes are all effective, the current reference probe is not switched; if two probes are effective or one probe is effective, the reference probe is switched to the effective probe; if the reference probe is effective, the reference probe is not switched. The application has the advantages that the reference probe is ensured to be in an effective state, the output of the fusion star sensor can be corrected in real time, and the star sensor output precision is ensured.