90 results about "Kinematic modeling" patented technology

The invention relates to the technical field of underwater navigation, and discloses a real-time attitude estimation method of an underwater inertial navigation system. The method comprises the steps that the underwater vehicle collects multi-axis angular velocity and linear acceleration data through an inertial measurement unit and uploads the data to a central processing module, and the central processing module conducts kinematics modeling on the data to generate attitude change initial feature vectors; receiving water flow velocity data of a Doppler velocimeter and pressure data of a depth sensor, and performing flow field interference compensation optimization on the attitude change initial feature vector based on the data to generate an anti-interference attitude feature vector; fusing the anti-interference attitude feature vector and a historical attitude estimation result to generate space-time fusion attitude state representation, and then resolving a real-time Euler angle through a nonlinear filter; and matching a corresponding attitude stability control instruction from the navigation strategy library according to the real-time Euler angle, and issuing the attitude stability control instruction to a propeller execution unit. The method can effectively cope with underwater complex environment interference and guarantee stable operation of the underwater vehicle.

The invention relates to the technical field of automatic laying of composite materials, in particular to an automatic compensation method, system and equipment for errors between silk laying belts and a storage medium. The method for compensating the error between the automatic silk laying belts comprises the following steps: establishing a mathematical mapping relation between the error compensation amount between the belts and robot control parameters through a standard sample piece laying test, and forming an error compensation theoretical model; the method comprises the following steps: aiming at a robot type fiber placement machine structure, constructing an inter-band error model based on pose kinematics modeling, robot and additional axis multi-axis interpolation modeling and error vector decomposition; the tail end target position, the attitude angle and the error compensation amount in the laying program are read in real time, and real-time control input is obtained; and on the basis of the error model, the corrected tail end position is inversely solved into a real-time adjustment angle of each joint, a robot inverse solution algorithm is corrected, and a joint control instruction is generated. According to the automatic tow belt laying device, the laying position precision of the automatic tow belt laying can be remarkably improved.

The invention discloses a forward and reverse design and simulation method for virtual excavation of a sunken vertical shaft heading machine. The method comprises the following steps: S1, initializing a terrain; s2, kinematic modeling of the heading machine; s3, track surface generation and virtual excavation; s4, forward design; s5, carrying out reverse design; and S6, outputting data. According to the forward and reverse design and simulation method for virtual excavation of the sinking type vertical shaft heading machine, geometric-level virtual excavation simulation can be realized based on geometric parameters, a kinematic model and stratum data of a VSM; the excavation effect of the preset excavation parameters can be verified through forward design, and a feasible excavation parameter set can be intelligently and reversely solved from the target excavation morphology through reverse design; and meanwhile, a standardized geometric model and structured data which can be directly used for subsequent engineering numerical analysis and construction guidance can be exported, so that the parameter determination precision, the process controllability and the scheme optimization capability before construction are improved.

The invention belongs to the technical field of mechanical arm joint control, and particularly discloses a preset performance self-adaptive joint control method for a rope-driven super-redundant snakelike mechanical arm, and the method comprises the following steps: carrying out kinematics modeling on a rope joint link of the rope-driven super-redundant snakelike mechanical arm, determining a relation between a rope speed and a joint angle, and determining a preset performance of the rope-driven super-redundant snakelike mechanical arm; calculating a joint jacobian matrix; designing a joint angle controller, defining an angle error and constraining the angle error in a preset performance range, and obtaining control input through an error transformation and return-to-zero dynamics principle so as to realize joint angle control; according to the method, a joint Jacobian matrix is estimated on line, and the joint Jacobian matrix is dynamically updated according to a rope speed error and a return-to-zero dynamic theory so as to adapt to the flexibility, time-varying characteristics and external disturbance of a rope, and the control precision is ensured. According to the method, it can be guaranteed that the joint angle of the rope-driven super-redundant mechanical arm can be accurately controlled under different working conditions, and it is guaranteed that the mechanical arm completes high-precision operation under the complex working conditions.

The invention relates to the technical field of automatic guided vehicle control, in particular to a multi-differential wheel set AGV trajectory tracking method and system, and the method comprises the steps: building a special kinematics forward / inverse solution model, and determining the speed and angle mapping relation between a driving wheel and the center of a vehicle body; constructing a double-layer framework of upper-layer pure tracking trajectory tracking and lower-layer wheel set cooperative control, and introducing a steering cooperative optimization strategy; an intelligent self-correction mechanism is set, and a strong correction mode or a smooth correction mode is selected according to the deviation distance; and deep fusion of a pure tracking algorithm and a special chassis is realized, and a complete closed-loop control system is formed. The system comprises a chassis module, a kinematics modeling module, a double-layer control module, a self-correction module and a closed-loop feedback module. According to the method, the problems of poor adaptability, motion coupling, unbalanced heavy AGV tracking precision and stability and the like of a traditional algorithm are solved, high-precision trajectory tracking is realized, tire wear and energy loss are reduced, the robustness of the AGV in a complex environment is enhanced, and the method is suitable for heavy and heavy-load AGVs.

The invention discloses an IMU (Inertial Measurement Unit) drift error calibration method for long-term attitude measurement of an industrial robot. The IMU drift error calibration method comprises the following steps: deducing a pose matrix between a robot base coordinate system and a navigation coordinate system; deriving a pose matrix between a robot tail end coordinate system and a sensor body coordinate system; kinematics modeling is conducted on the industrial robot, and motion parameters are obtained; deriving a homogeneous transformation matrix between two adjacent joints according to the kinematic parameters; acquiring actual joint corner information when the robot runs and actual information measured by a tail end IMU when the robot runs; wherein the actual information of the IMU comprises actual angular velocity information and actual attitude information; the collected actual joint rotation angle information is substituted into the homogeneous transformation matrix, theoretical attitude information of the tail end of the robot is obtained, and the theoretical attitude information is converted into a navigation coordinate system; converting the theoretical attitude information converted into the navigation coordinate system into an Euler angle; designing a Kalman filter; according to a Kalman filter, data fusion of theoretical attitude information and actual attitude information is completed, and calibration is achieved. According to the method, joint angle information, the industrial robot end theoretical attitude obtained through forward kinematics calculation of the kinematics model and actual attitude data obtained through IMU measurement are fused, and accumulated error calibration formed in long-term attitude measurement of the IMU is achieved.

The invention discloses a joint calibration method based on a rotary laser radar and a camera, and the method comprises the following steps: S1, carrying out the kinematic modeling of the camera, the laser radar and a motor rotating shaft based on a DH parameter method; s2, collecting synchronous laser radar point cloud data and camera image data of a motor rotating shaft at different angles; s3, processing the laser radar point cloud data; s4, processing the camera image data; s5, projecting the extracted laser point cloud depth continuous edge features to an image plane based on a current external parameter estimation value, and matching and associating the extracted laser point cloud depth continuous edge features with the image edge features extracted in the step S4; s6, constructing a projection residual equation about the external parameters according to the successfully matched feature pairs; and S7, the residual equation is linearized. According to the joint calibration method based on the rotary laser radar and the camera, high-precision and high-robustness automatic calibration is completed in an environment without an auxiliary target through kinematics modeling of a system and an advanced feature extraction matching technology. The invention further discloses a joint calibration device and system based on the rotary laser radar and the camera, and a storage medium.

The invention relates to a human body multi-cycle gait track prediction method based on small sample space-time decoupling. The method comprises the following steps: firstly, obtaining a single-cycle gait sample through kinematics modeling and cycle segmentation, and extracting, expanding and normalizing parameters such as stride and stride frequency; secondly, establishing a gait parameter joint distribution model by using a Gaussian mixture model and Gaussian mixture regression, and predicting gait parameters according to the target speed; and then space and time decoupling reconstruction is carried out, a high-fidelity joint trajectory is generated by adopting an adaptive collaborative attention LSTM network in space, a zoom factor is calculated based on a predicted stride frequency and a target speed in time, a time sequence is adaptively adjusted through a dynamic motion primitive, and finally a multi-period and multi-speed high-fidelity gait trajectory is generated through fusion. The method has high precision, interpretability and strong generalization ability under the small sample condition, the generated gaits are natural and coordinated and accord with the biomechanical law, and the application cost of a humanoid movement device is remarkably reduced.

The invention relates to the technical field of intelligent control, and particularly to a gantry platform kinematics modeling method considering parallelism and perpendicularity errors, which is applied to a gantry platform device. The gantry platform device comprises a crossbeam, a first guide rail and a second guide rail, one end of the crossbeam is in sliding fit with the first guide rail, and the other end of the crossbeam is in sliding fit with the second guide rail; the first guide rail is provided with a first longitudinal motor, and the second guide rail is provided with a second longitudinal motor; and the crossbeam is provided with a transverse motor configured to drive the gantry platform to move along the crossbeam. The method comprises: establishing a two-dimensional coordinate system; constructing a forward kinematics solution model; and constructing an inverse kinematics solution model.

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

The invention discloses a continuum robot position tracking and joint limiting avoidance method, and belongs to the field of robot control. According to the method, a current path is obtained through forward kinematics modeling, joint limiting constraint and ideal path generation are combined, a nonlinear programming problem with the maximum path deviation and the minimum path deviation as the target is constructed, and joint increment is iteratively solved to achieve end tracking and overall path fitting. According to the method, the problem that inverse kinematics is difficult to solve is avoided, joint overrun is explicitly avoided, and the method is suitable for high-precision and high-reliability control in a narrow space and an obstacle environment.

Disclosed are a rigid-flexible coupling continuum robot unit and a continuum robot. In the rigid-flexible coupling continuum robot unit, structural unit blocks are connected to each other in an interlaced manner to form a whole mechanical arm; a flexible nickel-titanium rod is connected to two adjacent structural unit blocks at two ends, respectively; a front-end unit block is arranged at the frontmost end of the mechanical arm; and a rear-end unit block is arranged at the rearmost end of the mechanical arm. In use, the memory alloy nickel-titanium rod forms a flexible joint, a limiting clamping jaw and a limiting boss form a rigid joint, the two joints complement each other, after a driving wire exerts a pressure, the limiting clamping jaw and the limiting boss are in a wrapping relationship, the movement track of the robot unit is limited, the robot unit always rotates along a circular arc around a rotation center, and the robot unit has the advantages of simple and accurate kinematic modeling, strong torsion resistance, strong load bearing capacity and the like, and is suitable for operation in various complex environments.

The invention relates to the technical field of intelligent manufacturing, and discloses an enterprise production data traceability control method based on artificial intelligence, and the method comprises the steps: actively implanting a digital coding disturbance sequence as a physical traceability fingerprint, and combining with kinematics modeling based on a Lagrange view angle, thereby achieving the traceability control of enterprise production data. Compared with a traditional statistical matching method which only depends on waveform geometric similarity, the method has the advantages that a physical sensing time sequence alignment mechanism is constructed, a time mapping path is forcibly required to follow the displacement conservation and entropy increase law, and the accuracy of the real-time tracking is improved. According to the technical scheme, mass balance verification is further utilized to carry out physical checking calculation on a traceability result, and the technical span from signal correlation advanced to physical causality effectively eliminates false alignment and quantization errors caused by shutdown and speed change, ensures absolute accuracy and non-tampering property of responsibility entity locking, and improves the reliability of the system. And the robustness and legal credibility of the industrial data management and control system are greatly improved.

The invention discloses a kinematics semi-analytical modeling method and terminal for a human wrist-simulated parallel mechanism, and the method comprises the steps: constructing a global coordinate system, a first coordinate system and a second coordinate system when the wrist parallel mechanism is subjected to kinematics positive solution, and then obtaining a target D-H expression corresponding to the tail end pose of the human wrist-simulated parallel mechanism, a target D-H expression is obtained, the target D-H expression shows the relation between the tail end pose and a first joint angle and the relation between the tail end pose and a second joint angle, then a target modular length expression is obtained, the target modular length expression shows the relation between a first modular length and the first joint angle and the relation between a second modular length and the second joint angle, and finally, the target D-H expression shows the relation between the tail end pose and the second joint angle. And obtaining numerical values of a first modulus length and a second modulus length, and substituting the numerical values of the first modulus length and the second modulus length into the target D-H expression and the target modulus length expression to obtain a tail end pose. The invention provides a solution capable of completing operation on a low-computing-power platform for a parallel mechanism simulating a human wrist.

The invention discloses a method for analyzing the influence of a rod length error and a kinematic pair gap on the motion of an ornithopter. The method comprises the following steps: carrying out kinematic modeling on an ornithopter structure to obtain a kinematic model; acquiring a motion trail of the end point of the tail end of the outer wing in the kinematic model as a first influence factor; the average flapping position change of the rod piece at the tail end of the outer wing is obtained in the kinematic model to serve as a second influence factor; performing margin modeling on the ornithopter structure in combination with the first influence factor and the second influence factor to obtain a margin model; and performing reliability solution analysis on the input ornithopter to be analyzed according to the margin model. According to the method, the error influence can be accurately captured, and the actual working state of the ornithopter can be more accurately reflected by defining the motion trail of the end point of the tail end of the outer wing and the average flapping position change of the rod piece at the tail end of the outer wing as influence factors of specific reliability. The two indexes are directly associated with the key parameters of the flight performance of the ornithopter, thereby ensuring that the evaluation of the system reliability is closer to the reality.

The invention discloses an intelligent steer-by-wire automatic parking method for a semitrailer, which comprises the following steps of: S1, modeling a parking environment, defining a vehicle state and performing kinematics modeling; s2, generating a parking path based on a mixed A * algorithm; and S3, designing a target function and carrying out optimization solution by utilizing a model prediction control algorithm to realize rolling optimization of the automatic parking process. According to the intelligent steer-by-wire automatic parking method for the semitrailer, autonomous parking control of the semitrailer in a complex environment is achieved, and automatic collision avoidance, posture adjustment, path minimization and cost control are achieved in the parking process.

The invention discloses an endoscope active following motion control method, which comprises the following steps of: 1, carrying out kinematics modeling on a continuum endoscope, obtaining a pose transformation matrix of the continuum endoscope so as to obtain a working space of the continuum endoscope, and verifying a reachable range of the working space in an eyeball; step 2, constructing a visual servo following controller based on the endoscope image, collecting the endoscope image and identifying the tip of the surgical instrument in the endoscope image based on an image processing algorithm of a YOLO neural network architecture; and extracting the deviation between the pixel space coordinates of the feature points and the expected features in real time, and controlling the camera at the tail end of the continuum endoscope to move based on the deviation of the feature points until the image features reach a target state. The multi-view intraoperative image can be provided in the continuous bending movement process of the continuum endoscope, the tail end of a surgical instrument is followed in real time in the operation, the posture of the surgical instrument in the operation is observed in real time, and the automation degree of the continuum endoscope is improved.

The application discloses a kind of unmanned aerial vehicle cluster formation fault-tolerant method based on original pigeon chaotic adaptive sliding mode control, including the following steps: step one: the kinematics of unmanned aerial vehicle is modeled, the initial state of unmanned aerial vehicle is determined and the formation flight control system of wingman and long machine;Step two: introduce the virtual reference unmanned aerial vehicle dynamics model, design tracking error, obtain dynamic tracking error equation, ensure the accuracy of reference model;Step three: design sliding mode surface function, obtain reduced order sliding mode kinematics equation by using adaptive sliding mode control technology;Six steps such as.The method of the application is simple, the proposed chaotic pigeon group mechanism can greatly optimize the parameters in adaptive control and sliding mode control parameters, increase the control convergence speed, and give a robust solution to the difficult problems such as unmanned aerial vehicle unable to adapt to complex environment due to communication failure.

The present invention belongs to the field of autonomous driving control technology, and specifically relates to an autonomous driving vehicle trajectory tracking method, system and vehicle based on improved backstepping control. The method establishes a vehicle kinematic model, defines an error dynamic equation, introduces virtual feedback variables to simplify the backstepping control design, combines the control law to design speed and steering angle control quantities, and performs input constraint processing at the same time. The system includes kinematic modeling, error dynamic equations, virtual feedback variable generation, control law design, input constraint processing and trajectory tracking execution module. The vehicle is integrated with the system to achieve accurate trajectory tracking. The present invention reduces computational complexity, takes input constraints into account, improves convergence speed, enhances system robustness, and effectively solves the technical problems of traditional methods with complex design and low computational efficiency in high-dimensional systems, thereby improving the safety and reliability of autonomous driving vehicles.

The invention relates to the technical field of automation equipment control, in particular to a multi-dimensional configuration description and modeling method for an industrial robot, and solves the problems that only kinematics modeling can be performed and peripherals, communication and machining programs cannot be covered in the prior art. The method comprises the following steps of S1, dividing independent functional parts of an industrial robot machine into peripheral parts, communication parts and basic parts according to function uniqueness; s2, an object-oriented modeling method is used for modeling the three types of components from the dimensions of motion ability, function interface and interaction logic; s3, modeling results are integrated, the basic part is used as a carrier, peripheral and communication part modeling data and configuration parameters are matched, a machining program is designed in a flow chart compiling mode, and a configuration description file set is generated; and S4, loading the file set to a development platform program, controlling industrial robots with different configurations, and supporting construction of digital twin objects. According to the method, a multi-dimensional modeling system is constructed, a physical structure and motion logic are covered, key production links are incorporated, and model description and whole-process control are realized.

The invention discloses a mechanical arm kinematics modeling and motion control method, device and system. The mechanical arm comprises N joints connected in series and a sand disc connected to the tail end, and a radial distance R exists between the working edge of the sand disc and the tail end arm section. The kinematics equation construction method comprises the following steps: determining a working edge reference point of a sand disc as a motion control target; based on mechanical structure parameters, joint variables and a radial distance R of the mechanical arm, forward and inverse solution equations of the kinematics position, speed and acceleration of a working edge reference point are deduced. The motion control method comprises the following steps: acquiring a discrete expected position, speed and acceleration point; calculating an expected joint angle, angular velocity and angular acceleration by using a position inverse solution equation, a velocity inverse solution equation and an acceleration inverse solution equation in sequence; and giving a calculation result to a multi-axis motion controller in real time. According to the method, the radial distance of the sand disc is incorporated into the kinematics model, feedforward control of three levels of position, speed and acceleration is achieved, and the motion control precision of the non-standard mechanical arm is remarkably improved.

This invention belongs to the field of intelligent manufacturing technology and discloses a real-time data-driven intelligent digital twin system for the docking of aerospace components. First, a standardized communication interface is established between multi-source sensors and various modules of the system to collect and transmit sensor data in real time. Second, based on the real-time multi-axis displacement data of the positioner, the real-time motion trajectory of the component is derived through kinematic modeling, completing the spatial pose parameter calculation of the component. Finally, the component pose parameters and multi-dimensional force sensing data are fused to construct a dynamic and interactive three-dimensional digital twin interface, realizing twin monitoring of the component's motion state and internal forces during the docking process. This system, based on the Unity3D engine, achieves real-time synchronous mapping of multi-dimensional force information and motion attitude parameters. Through a closed-loop processing flow of data acquisition, analysis, and visualization, it realizes quality assessment and quantitative analysis of the aerospace component assembly process, significantly improving the controllability of the docking process.

This invention discloses a method for inverse kinematics modeling of a polyhedral mobile robot, comprising: S1, constructing a forward kinematics model of a polyhedral open-chain robot, defining a kinematic space with the edge lengths of a virtual polyhedron as the core, and establishing a mapping relationship between joint angles and the edge lengths of the virtual polyhedron; S2, constructing an optimization objective function based on the Hadamard product based on the error between the target edge length set and the actual edge length set of the virtual polyhedron; S3, generating an initial set of iteration points covering all quasi-convex regions in the joint space of the polyhedral open-chain robot; S4, solving the gradient of the objective function and iteratively updating the joint angles; S5, setting a convergence threshold and termination condition, performing convergence judgment on the iteration process, and selecting the optimal solution for inverse kinematics; This invention achieves accurate modeling of the inverse kinematics of a tetrahedral mobile robot by constructing an error optimization model based on the edge lengths of a virtual polyhedron and combining Monte Carlo sampling initialization and gradient descent iterative solution.

The invention discloses a positioning control method for accurate operation of a drill jumbo under complex working conditions, and aims to solve the technical problems of poor positioning accuracy and weak robustness of a traditional control method under the conditions of strong rock stratum disturbance, uncertain kinetic parameters, hydraulic driving nonlinearity and the like. Through kinematics modeling and dynamics simplification, complex dynamics characteristics of the mechanical arm are decomposed into internal parameter uncertainty (such as joint abrasion, hydraulic leakage and load change) and external strong interference (such as rock reaction force and high-frequency vibration impact). For internal nonlinearity and coupling terms, an RBF neural network (RBF-NN) is adopted to carry out online learning and approximation; aiming at external interference and neural network fitting errors, designing an extended state observer (ESO) to realize real-time compensation; and in combination with a self-adaptive Backstepping control strategy and a tracking differentiator (TD), a control framework of internal and external disturbance joint estimation and compensation is constructed, and high-precision trajectory tracking of an end effector of the mechanical arm is ensured. The method is suitable for precise control of high-degree-of-freedom engineering equipment in severe environments such as mines and tunnels.

The invention relates to an AGV path tracking method based on an improved LQR, and the method comprises a kinematics modeling module, the output end of the kinematics modeling module is electrically connected with a multi-sensor fusion positioning module, and the output end of the multi-sensor fusion positioning module is electrically connected with an improved LQR control module. The output end of the improved LQR control module is electrically connected with an execution control module. High-precision positioning is realized through extended Kalman filtering, the improved LQR control module solves and generates an optimal control instruction by optimizing a target function and a Riccati equation, and when it is detected that tracking deviation exceeds a limit or a sensor is abnormal, a control strategy can be automatically switched to ensure operation safety, and the positioning accuracy is improved. By means of the man-machine interaction design, an operator can flexibly adjust control parameters according to actual working conditions, the adaptability and usability of the system are improved, and comprehensive improvement of AGV path tracking in the aspects of control precision, stability and adaptability is achieved through algorithm innovation and system optimization.

This application relates to a method, apparatus, and surgical robot for generating control information for a robotic arm. The method includes: determining a target operating position; determining motion control information for the robotic arm based on the target operating position through kinematic modeling; inputting the motion control information into a pre-trained neural network model to obtain a predicted operating position corresponding to the motion control information; if, based on the target operating position and the predicted operating position, the predicted operating position does not meet the requirements, adjusting the motion control information and inputting the adjusted motion control information into the neural network model to obtain a predicted operating position corresponding to the motion control information; until, based on the target operating position and the predicted operating position, the predicted operating position meets the requirements, the final adjusted motion control information is used as the control information for the robotic arm. This method can improve the control accuracy of the robotic arm.

The application provides a sand suction and filling multi-arm cooperative control algorithm based on kinematics and dynamics coupling, comprising the following steps: S1: water dynamic disturbance field full working condition data acquisition and feature library construction; S2: multi-arm kinematics modeling and unified mapping of working space; S3: construction of a multi-arm kinematics-dynamics coupling model embedded with a water dynamic disturbance adaptive compensation term; S4: multi-arm task-dynamics coupling distribution based on an improved parasite-prey algorithm; S5: trajectory-task bidirectional coupling planning based on a fractional order pseudospectral method; S6: multi-arm-filling cooperative closed loop control based on a port-controlled Hamilton fractional order passive control; and S7: real-time acquisition of sand suction and filling parameters and full system closed loop feedback. Through deep coupling modeling of kinematics and dynamics and bidirectional cooperative optimization of core control algorithms, the application realizes high-precision, high-stability and high-efficiency cooperative control of multi-arm sand suction and filling operation in a dynamic water environment.

The invention relates to a method and a device for perineal prostate needle biopsy. In one embodiment, the device for perineal prostate needle biopsy comprises: (a) a first parallel mechanism for translating or rotating an ultrasonic probe; (b) a series-parallel hybrid mechanism as an end effector of the first parallel mechanism for accommodating the ultrasonic probe and a puncture needle introducer; (c) a driving module of the series-parallel hybrid mechanism for driving the ultrasonic probe to rotate and translate along the axis of the ultrasonic probe; (d) a second parallel mechanism of the series-parallel hybrid mechanism for controlling the configuration of the puncture needle guider relative to the ultrasonic probe and limiting the motion trail of the puncture needle within the axial imaging plane of the ultrasonic probe; and a controller for executing a kinematic modeling method.

The invention discloses an in-situ detection mechanical arm control method and system. The method comprises the steps that a six-degree-of-freedom mechanical arm kinematic model is constructed based on the Lie group theory; acquiring operation state data of the mechanical arm; utilizing a CNN-LSTM time sequence fault diagnosis model to identify a potential fault; generating a dynamic environment response control decision based on reinforcement learning; dynamically adjusting control parameters by combining a fault type, a control decision and a kinematic model; and the mechanical arm is driven to execute operation and feed back the state. The system comprises a Lie group kinematics modeling unit, a multi-parameter state acquisition unit, a CNN-LSTM fault diagnosis unit, a reinforcement learning decision unit, a dynamic parameter adjustment unit and an execution and feedback unit. According to the method and the system, the pose control precision, the fault identification timeliness and the environmental adaptability of the mechanical arm are improved, and efficient and stable in-situ detection is ensured.

The invention discloses an automatic measurement simulation platform for large components. The automatic measurement simulation platform comprises an equipment modeling module, a simulation scene loading module, a feature extraction module, a measurement planning module and a measurement execution module, the equipment modeling module is used for carrying out kinematics modeling on measuring equipment and carrying equipment of large components and constructing a measurement constraint model and a combined measurement constraint model of each measuring equipment; the simulation scene loading module is used for constructing a large component automatic measurement scene, loading equipment and a large component model; the feature extraction module is used for selecting a to-be-measured appearance feature surface through interactive feature recognition and performing feature extraction on the selected feature surface; the measurement planning module is used for performing scanning path planning and station planning; and the measurement execution module is used for driving the equipment model to move in the simulation scene according to the planning result, dynamically demonstrating the simulation process and outputting a measurement result. According to the invention, a large component measurement scene and equipment movement can be accurately simulated, and feature extraction and measurement planning are automatically completed.