3936 results about "Position fixing" patented technology

The invention discloses a vehicle-mounted Beidou positioning deviation self-calibration system fused with inertial navigation information, and relates to the technical field of navigation and positioning. The method is used for solving the problems of positioning deviation accumulation and signal failure in a complex environment. The system realizes space-time alignment of inertial navigation and Beidou observation data through timestamp interpolation and coordinate system conversion, and constructs a multi-source synchronous data stream. A difference value between an inertial navigation calculation speed and a Beidou Doppler speed is analyzed based on a vehicle incomplete constraint model, and a weight factor is generated in combination with a confidence threshold to suppress abnormal observation. A geometric matching error is calculated through a high-precision lane map curvature and a vehicle steering angle, and candidate tracks are screened to generate transverse calibration parameters. The noise covariance is dynamically adjusted through a tight coupling filtering algorithm, the mode is switched to a lane constraint calibration mode when a Beidou signal is interrupted, inertial navigation errors are compensated through error boundary constraint, and stable output is achieved. Multi-source data deep fusion and adaptive robust calibration are realized, and system robustness and positioning continuity are improved.

The invention belongs to the technical field of path planning, and discloses an unmanned driving dynamic path planning method and system based on multi-source data fusion, and the method comprises the steps: collecting an ice and snow pavement friction coefficient, a curve curvature and an obstacle point cloud, constructing a sensor confidence coefficient matrix, generating a fused semantic map, and constructing a dynamic environment semantic model. Outputting a real-time friction coefficient field and a risk thermodynamic map layer; the roadside unit broadcasts coordinates of opposite vehicles in a blind area of a curve to a vehicle end, constructs an ice and snow pavement offset crowdsourcing map, and generates a global-local fusion topology; fusing the real-time friction coefficient field and the global-local fusion topology to generate a smooth trajectory set, and further generating a risk optimal path instruction set; a steering angle and torque instruction is decomposed, positioning drift is compensated in real time, and a normal mode for updating the vehicle positioning state and a degradation mode when the millimeter wave radar fails are constructed; and generating execution logs and health state vectors, and aggregating the execution logs and the health state vectors of multiple vehicles to form closed-loop iterative update.

The invention discloses a fusion optimization method based on Kalman filtering and LSTM cascade. The fusion optimization method comprises three steps of dynamic state estimation, time sequence error modeling and closed-loop fusion optimization. IMU (Inertial Measurement Unit) data is used as input, dynamic state estimation is realized through Kalman filtering, modeling system errors are separated, an LSTM (Long Short Term Memory) network is used for carrying out time sequence modeling on a residual error sequence to capture nonlinear errors, and finally, a corrected state quantity is fed back to a Kalman filtering updating link through a closed-loop feedback mechanism. And collaborative optimization of error compensation and state estimation is realized. According to the method, IMU error accumulation is effectively inhibited through a dynamic-data dual-drive mechanism, the navigation precision and robustness in a complex scene are remarkably improved, and the requirements of high-dynamic applications such as intelligent driving and unmanned aerial vehicle navigation can be met. Finally, the optimized IMU data and the GNSS observation value are fused for integrated navigation, high-precision navigation solution is achieved through Kalman filtering, and indoor and outdoor seamless positioning and the all-attitude control requirement of a high-dynamic carrier are met.

The present application relates to PPP-RTK, RTK, SSR, or like correction data based devices and methods to produce geolocation solutions with improved accuracy. Further, such devices and methods may be further employed in various related utility locator devices, utility locating transmitters, and other utility locating and mapping devices.

The invention discloses a vehicle positioning method and system based on UWB and vehicle constraint, and relates to the field of vehicle positioning, and the method comprises the steps: deploying a UWB reference station in a well mining environment, and enabling a vehicle to be provided with a UWB tag; obtaining distance measurement data of at least two UWB reference stations, and detecting and compensating the distance measurement data to obtain a vehicle UWB position; collecting vehicle-mounted IMU (Inertial Measurement Unit) data, and obtaining a vehicle attitude quaternion through attitude calculation; collecting vehicle wheel speed meter data, and correcting the vehicle wheel speed meter data according to vehicle motion constraint conditions; according to the vehicle UWB position, the vehicle attitude quaternion and the corrected vehicle wheel speed meter data, the vehicle position is obtained through an adaptive Kalman filtering fusion algorithm. Aiming at low positioning precision caused by easy accumulation of errors and drifting of a traditional inertial navigation system in a well mine closed space in the prior art, the invention reduces the influence of a multipath effect in the traditional inertial navigation system on the positioning precision.

The invention discloses a navigation matching correction method based on an inspection robot, and the method comprises the steps: building a feature database through the deployment of a physical calibration object and the recognition of a natural feature object, providing a reliable positioning reference for a robot, achieving the coarse positioning through the fusion of visual and laser radar data in a positioning process, and introducing a dynamic credibility evaluation mechanism. The positioning reliability is quantified in real time through an exponential decay model, when the credibility is lower than a threshold value, the system automatically triggers a compensation behavior to re-search features, in the aspect of multi-robot cooperation, secondary positioning correction is achieved through track matching and data fusion, high-confidence-coefficient reference data are screened through a clustering algorithm, the group positioning precision is improved, and the positioning accuracy is improved. Aiming at a key inspection area, multi-angle image matching is adopted to realize fine positioning, a positioning error is dynamically corrected through a sliding window, the continuity and accuracy of robot navigation in a complex environment are remarkably improved through closed-loop correction and self-adaptive optimization, and the method is suitable for intelligent inspection requirements of railway trains.

The invention discloses a polling path dynamic planning method, medium and equipment, and the method comprises the steps: obtaining environment information in real time, dynamically switching an RTK-GPS mode, a visual inertial navigation mode and a laser SLAM positioning mode, generating the current positioning information of a robot in combination with a global map, and constructing a local environment map; and planning an adaptive second preset inspection path based on the first preset inspection path. Environmental feature information is actively collected in an outdoor environment, a real-time obstacle avoidance path is generated by dynamically updating a local environment map, and the real-time obstacle avoidance path is fused to a second preset inspection path, so that smooth switching and dynamic obstacle avoidance cooperation of a positioning mode in an indoor and outdoor scene are realized; the problem of planning failure caused by multiple positioning source conflicts, local path oscillation and environment sudden change in a complex scene is solved, and the continuity of the inspection process and the path planning robustness are guaranteed.

The invention relates to the technical field of calibration test, and particularly discloses a strapdown inertial navigation automatic calibration test method of a temperature control biaxial rate position turntable. Comprising the following steps: S1, multi-dimensional error modeling and layered calibration architecture: constructing a comprehensive error model containing a sensor scale factor error, an installation non-orthogonal error, a zero offset error, a cross axis coupling error and a temperature related error; s2, a wide temperature range self-adaptive compensation mechanism: carrying out heat preservation at a preset temperature point and executing turntable positioning and rate movement; s3, performing automatic data processing and parameter estimation; and S4, performing real-time error correction and dynamic verification: performing real-time error correction based on the estimated parameters, and evaluating navigation performance indexes such as position, speed and attitude precision. Through technical innovation, high-precision, automatic and wide-temperature-range calibration of the strapdown inertial navigation system is realized, and the method is suitable for aerospace, intelligent equipment and other scenes with strict navigation precision requirements, and has remarkable engineering application value and market competitiveness.

The invention provides a high-precision perception-driven automatic driving positioning method and system, and relates to the technical field of automatic driving, and the method comprises the steps: collecting vehicle environment data in real time through a multi-mode sensor array, and generating a multi-source perception data set; performing time-space synchronization processing; performing motion distortion correction on the fused sensing data stream to generate dynamic compensation sensing data; inputting a multi-source fusion positioning model, and performing three-dimensional space matching in combination with high-precision map data to obtain real-time positioning coordinates; and performing iterative optimization on the real-time positioning coordinates through an adaptive error correction module to generate a vehicle positioning result. According to the method and the device, the technical problem that the positioning precision is affected due to data distortion caused by the influence of the vehicle motion on the sensor data is solved, the distortion caused by the vehicle motion is eliminated through motion distortion correction and compensation, and the positioning precision and stability are improved.

The invention provides an unmanned ship charging cable control method based on visual identification, and relates to the technical field of data processing, and the method comprises the steps: collecting continuous image frames of an unmanned ship charging area, identifying the spatial displacement and inclination angle change of an unmanned ship, analyzing the attitude offset of the unmanned ship caused by sea waves, calculating a water surface disturbance factor, and calculating the water surface disturbance factor. The method comprises the following steps: identifying the position of a charging interface, obtaining an initial positioning coordinate, carrying out prediction analysis on a disturbance trend in a preset time window, predicting a position change range of the charging interface, obtaining prediction coordinate data, planning a butt joint path of a cable and the charging interface, obtaining a compensation path sequence, and generating a cable propulsion instruction. And collecting an area image of the charging interface to obtain path tracking image data, judging whether the butt joint of the charging interface is successful or not, and if not, dynamically correcting the compensation path sequence. According to the invention, the cable is controlled through visual identification to charge the unmanned ship.

The invention provides a road marking quality intelligent evaluation system based on image analysis, and relates to the technical field of road facility monitoring, and the system comprises a detection unit, a marking quality evaluation unit, a marking wear prediction unit, a GPS positioning unit, a vehicle driving information unit, a control unit and a remote central control unit. The marking quality evaluation unit is constructed based on a differential geometry theory and comprises a curvature flow edge detection module, a marking geometric characteristic manifold representation module and a multi-scale differential invariant evaluation module, the system regards a marking as a two-dimensional manifold, and the marking quality is evaluated by calculating differential geometric quantities such as a Gaussian curvature, an average curvature and a shape index. And constructing geodesic distance measurement on the feature manifold, and evaluating the completeness, visibility and reflective performance of the marked line. And the marking wear prediction unit predicts the service life of the marking based on the traffic flow information and the environment characteristic mapping relation model, and generates a maintenance suggestion.

The invention discloses a method for determining the distance between blasting unit groups for a surface mine, a rapid adjusting device and a blasting operation system. The determination method comprises the following steps: acquiring multi-dimensional data through a geological radar, a sensor and the like, and constructing a model through normalization processing; a finite element-discrete element coupling algorithm is adopted to carry out three-dimensional geology-blasting coupling modeling, an improved NSGA-III algorithm is combined to solve a multi-objective function to determine an optimal interval, and Kalman filtering is utilized to realize real-time feedback correction. The rapid adjusting device comprises a multi-angle adjusting module, an intelligent navigation module and a cooperative control module, and accurate positioning and rapid adjusting can be achieved. According to the method, a modeling-calculating-adjusting-feedback full-process automatic system is formed, and compared with a traditional technology, the lumpiness qualification rate can be increased by 25% or above, the interval adjusting time is shortened to be within 15 minutes, and the mine blasting efficiency and safety are effectively improved.

The invention provides a tunneling equipment autonomous navigation positioning method and system based on multi-source data, and relates to the technical field of inertial navigation, the method comprises the following steps: connecting multi-source monitoring equipment, obtaining a multi-source data set, carrying out space-time alignment, and establishing a monitoring data network; butting the transparent geologic model, and fusing the transparent geologic model with a monitoring data network to construct a virtual model; fitting the physical structure parameters and the operation state parameters of the tunneling equipment to the virtual model, positioning the tunneling equipment, and performing tunneling path optimization search; performing attitude and inertia analysis in the virtual model based on the planned path to obtain a path attitude strategy; and carrying out operation navigation control on the tunneling equipment. According to the method and the device, the technical problem of high difficulty in long-time navigation and positioning in a complex environment due to lack of autonomous navigation of the tunneling equipment is solved, and accurate positioning of the tunneling equipment in the complex environment is realized through fusion of multi-source monitoring and the virtual model, so that the tunneling efficiency and safety are improved.

The invention discloses an ocean multi-mode environment perception and intelligent ship navigation decision-making method based on a double-branch vision-semantic encoder. The method comprises the following steps: S1, acquiring a multi-source data image containing a ship and a surrounding environment thereof from an existing public maritime data set or platform; s2, training a double-branch vision-semantic encoder by using the multi-source data image, and inputting a to-be-processed image extracted in real time into a multi-modal feature matrix in the trained double-branch vision-semantic encoder; s3, based on the multi-modal feature matrix, obtaining positioning information of the ship and surrounding environment elements, and constructing a dynamic security domain model; and S4, in combination with the dynamic security domain model and the multi-ship relative position relationship, carrying out quantitative evaluation on the navigation risk, and generating a self-adaptive navigation strategy based on an evaluation result. According to the invention, high-precision ship positioning and environment element identification under complex weather and illumination conditions are realized by using all-weather characteristics and multi-scale visual feature coding of SAR imaging.

The invention discloses a vehicle navigation positioning method and system when a navigation signal is lost, and relates to the technical field of vehicle autonomous localization, and the method comprises the steps: carrying out the tight coupling matching based on a geomagnetic feature map, obtaining the geomagnetic sequence similarity through a sliding window dynamic time warping algorithm, and generating a fusion positioning track; extracting a road network topology connection relation from the high-precision map, constructing a road connection graph Laplacian matrix with a weight, and obtaining a topology constraint correction coefficient through a graph convolutional network in combination with the fusion positioning track; and constructing a joint optimization function based on the topological constraint correction coefficient, and solving an optimal positioning coordinate by adopting an asymmetric Gaussian-Newton iterative algorithm. According to the method, the defects of topology modeling stiffness and non-linear optimization instability of a traditional method are overcome, so that high-precision and high-robustness vehicle continuous positioning is realized in a GNSS signal loss scene.

The invention discloses a high-precision train locomotive positioning method and system based on a GNSS (Global Navigation Satellite System) and INS (Inertial Navigation Satellite System) loose combination mode, and the method realizes the precise positioning of a train by combining the data of an IMU (Inertial Measurement Unit) and a GNSS (Global Navigation Satellite System). The method comprises the following steps: firstly, acquiring IMU data, performing error correction, and outputting corrected acceleration and angular velocity; meanwhile, a GNSS signal is obtained and a pseudo-range measurement value is extracted. Then, inertial navigation calculation is carried out, including attitude calculation, position and speed calculation and sensor deviation updating; through Kalman filtering fusion, state estimation and error correction are carried out by using complementary characteristics of the INS and the GNSS, so that the positioning precision is improved. In the initialization stage, the normal work of the system is ensured through the installation and parameter setting of the IMU and the GNSS. Finally, through Kalman filtering processing, accurate train position, speed, attitude and sensor deviation data are output, and reliable data support is provided for a train control system.

The invention provides an unmanned aerial vehicle multi-mode navigation positioning method, device and equipment, and the method comprises the steps: obtaining GPS, inertia and visual navigation mode positioning data through determining a target positioning precision index, and carrying out the evaluation to generate a multi-mode navigation state set; performing performance competition on each navigation mode based on the state set, establishing an inter-mode negotiation mechanism, and determining a mode priority sequence; establishing a navigation mode credibility matrix in combination with the priority sequence, and establishing an adaptive weight distribution sequence; analyzing a weight change trend and mode switching resource overhead, carrying out navigation mode dynamic screening through switching cost quantitative evaluation, and determining a dominant navigation mode and an auxiliary navigation mode; and performing frequency characteristic analysis on the dominant and auxiliary modes, determining a frequency domain fusion strategy based on a frequency coherence coefficient, generating a fusion positioning track, and outputting a high-precision positioning result through precision evaluation to realize intelligent multi-mode navigation positioning.

The invention relates to the technical field of ship navigation system safety, and provides a Beidou satellite navigation deception detection method and system based on multi-source information, and the method comprises the steps: obtaining Beidou satellite navigation data, AIS information, navigation radar data and sea chart data; performing denoising processing on the Beidou satellite navigation data, and performing space-time compensation on the AIS information; clutter suppression is carried out on the navigation radar data; calculating ship body position deviation, and verifying the ship body relative position according to the ship body position deviation; calculating the real position of the ship body and the Beidou positioning deviation, and verifying the absolute position of the ship body; performing hull course consistency verification; and performing Beidou satellite navigation deception detection according to the ship body relative position verification, the ship body absolute position verification and the ship body course consistency verification. According to the invention, multi-dimensional detection is carried out on key information such as the position and course of the ship, so that the probability that the ship falls into danger due to wrong navigation signals is greatly reduced, and the navigation safety of the ship is guaranteed.

The invention discloses a transformer substation positioning and navigation method and system integrating positioning and visual auxiliary positioning. The method comprises the following steps: establishing a background electromagnetic field distribution baseline graph associated with a three-dimensional reference map; electromagnetic field data of the transformer substation in an emergency response mode is collected through the unmanned aerial vehicle, and the abnormal field intensity of a space electromagnetic field and a fault source pointing vector pointing to a fault source are calculated; constructing a risk adaptive elliptical forbidden zone; calculating a passage cost index Cto of the unmanned aerial vehicle passing through each three-dimensional grid in the three-dimensional reference map by using the fault source pointing vector and the risk adaptive elliptical forbidden zone; and searching a path which is from the current position of the unmanned aerial vehicle to a preset target point, bypasses the risk adaptive elliptical forbidden zone, faces the fault source and has the lowest total passing cost index Cto by adopting a preset path search algorithm. According to the method, the risk self-adaptive elliptical forbidden zone is constructed and is used as the three-dimensional grid forbidden assignment processing, so that the dynamic global path avoidance of the sudden dangerous zone is realized.

The invention relates to the technical field of information processing, in particular to a mine microseism positioning control system and method.The mine microseism positioning control method comprises the steps that microseism signals are synchronously collected through a geophone, an accelerometer, an acoustic emission sensor and an optical fiber sensor, and data timestamps are aligned based on a GPS / Beidou clock; blind source separation is carried out on the signals after wavelet filtering, independent seismic source components are extracted, multi-sensor features are fused through a graph neural network, and a space-time joint feature matrix is constructed; classifying micro-seismic event types by using a ResNet-LSTM hybrid model, generating a seismic source coordinate initial solution based on deep reinforcement learning, and iteratively converging to an optimal solution through a particle swarm optimization algorithm; and mapping a positioning result to a three-dimensional geological grid model, simulating an energy diffusion path, triggering a three-level alarm according to the event energy density, and automatically pushing an emergency instruction to a mine safety management system. Therefore, the problem of low precision of the existing mine microseism positioning control system is solved.

The invention discloses an underground vehicle positioning method based on visual target information fusion, and relates to underground vehicle positioning. The method comprises the steps that visual targets are arranged on the side wall and the top of an underground roadway at preset intervals; collecting multi-source sensor data; extracting a target ID (Identity) and a pixel coordinate # imgabs0 # of the target in an image coordinate system; according to the vehicle-mounted visual camera, converting the extracted pixel coordinate # imgabs2 # of the target into a three-dimensional coordinate # imgabs3 # under a camera coordinate system by using a pre-calibrated camera internal reference matrix K and an external reference matrix # imgabs1 #; querying target coordinates of the corresponding target in a world coordinate system from a database according to the target ID; according to the target coordinate and the three-dimensional coordinate # imgabs4 #, solving the position and attitude of the vehicle relative to a world coordinate system by solving an inverse projection problem, and obtaining a visual target positioning result; and performing multi-sensor fusion according to the recognition state of the visual target to obtain a vehicle positioning result. According to the method, the problems of large positioning accumulative error of the underground long and straight roadway and positioning sudden change caused by visual target misrecognition are solved.

The invention relates to the technical field of civil engineering construction, in particular to a precise positioning civil engineering pile foundation construction system which comprises a multi-source space sensing and positioning module, a space-time multi-dimensional data fusion module, a three-dimensional guiding and correcting module, a hydraulic control module and a closed-loop feedback optimization module. The multi-source space sensing and positioning module obtains pile machine position and attitude information through the Beidou / GNSS high-precision positioning unit, the inertia high-precision navigation unit and the laser horizontal measurement unit, and the space-time multi-dimensional data fusion module processes and fuses the information to generate unified space position data. The three-dimensional guiding and correcting module compares the data with preset pile position coordinates, if the deviation exceeds a threshold value, a correcting instruction is generated, the hydraulic control module executes the instruction and adjusts the position and the posture of a pile machine, the closed-loop feedback optimization module collects the data in the correcting process and optimizes a correcting strategy, all-weather centimeter-level precision space positioning is achieved, and the positioning precision is improved. And the accuracy and efficiency of pile foundation construction are improved.

Disclosed are an inertial baseline integrated navigation method, and a product, a medium, a device and an autonomous underwater vehicle, relating to the field of navigation. The method comprises: in an initial stage of the starting of an inertial baseline integrated navigation system, an SINS using a USBL to assist with initial alignment and obtaining initial attitude information (1); when the inertial baseline integrated navigation system enters a formal navigation operating state, the SINS performing pure inertial navigation solving on the basis of the initial attitude information, so as to obtain navigation parameter calculation values including errors (2), wherein the navigation parameter calculation values comprise the attitude, velocity and position; on the basis of the navigation parameter calculation values including the errors, constructing a navigation state error model based on a Lie group (3); on the basis of a Huber function, constructing a generalized maximum likelihood estimation model (4); according to the navigation state error model based on a Lie group and the generalized maximum likelihood estimation model, establishing an integrated navigation robust Kalman filtering algorithm (5); on the basis of the integrated navigation robust Kalman filtering algorithm, performing filtering estimation on the inertial baseline integrated navigation system, so as to obtain a state estimation value (6); and on the basis of the state estimation value, performing feedback updating on navigation parameters, and on the basis of the updated navigation parameters, performing navigation. The method can improve the integrated filtering precision and positioning and orientation precision.

The invention discloses an unmanned ship displacement attitude high-precision fusion method based on adaptive Kalman filtering, and belongs to the technical field of ship sensing positioning, and the method comprises the steps: building a discrete time state space model of a navigation data state through employing a discrete integration mode based on the navigation data state; obtaining a system state equation by means of a rotation matrix and a median theorem; obtaining an observation transfer matrix through coordinate system information, a geodesic line length between two points and an azimuth angle, and obtaining a state observation equation by combining noise data; based on the system state equation and the state observation equation, using an adaptive Kalman filtering algorithm to obtain displacement attitude information of the unmanned ship; detecting the prediction data of the unmanned ship by using a sliding window method; and when the predicted data is detected to be abnormal, substituting the predicted data into Kalman filtering for correction. According to the invention, through state modeling, fusion algorithm, anomaly detection and anomaly correction, the precision, reliability and robustness of obtaining the displacement attitude information of the unmanned ship are improved.

The invention discloses a satellite navigation positioning method and device and a storage medium. The positioning method comprises the steps that observation parameters collected by a mobile terminal in a preset epoch are obtained, the observation parameters comprise GNSS parameters and inertial navigation correlation parameters, and the GNSS parameters comprise GNSS prior parameters and GNSS posterior parameters; the observation parameters are input into a preset positioning precision evaluation model, a precision evaluation value is obtained, and the positioning precision evaluation model is obtained based on training of historical observation parameters collected by multiple epochs; determining whether the positioning information represented by the current observation parameter is accurate based on the precision evaluation value; when it is determined that the positioning information is inaccurate, a positioning result is determined based on a floating point solution of integer ambiguity; and when the positioning information is determined to be accurate, determining a positioning result based on the fixed solution of the integer ambiguity. The method has the technical effect of improving the positioning precision and the positioning reliability of the global satellite navigation system.

The invention relates to the technical field of ocean engineering construction, and discloses a construction positioning and SCADA visualization integrated intelligent arrangement method for an arrangement ship, which comprises the following steps: synchronously acquiring coordinates and attitude parameters of the arrangement ship through a Beidou positioning terminal and an inertial navigation device, and constructing a three-dimensional digital twinborn model of a construction scene in combination with submarine topography surveying and mapping data; analyzing boundary and gradient characteristics of the target arrangement area based on the model, and generating an initial arrangement path planning scheme; position deviation and ocean current flow velocity data are monitored in real time in the operation process, and the laying path is dynamically adjusted; and the position of the laying ship, the path adjustment record and the submarine topography change are displayed in real time through a visual interface of the SCADA system. According to the method, high-precision positioning, dynamic path optimization and full-process three-dimensional visual monitoring of the laying operation are realized, the problems of large positioning deviation and response lag of a traditional method are solved, and the construction precision and efficiency are remarkably improved.

The invention discloses a fluid loading and unloading arm dynamic flange automatic docking method based on image visual servo, which comprises the following steps: initializing the tail end position of a loading and unloading arm, and controlling the loading and unloading arm to move until complete image information of a flange to be docked can be acquired; the method comprises the following steps: acquiring an image of a flange to be butted, and extracting initial candidate circles with circle features in the image by adopting a Hough circle detection algorithm; through an RANSAC (Random Sample Consensus) algorithm, performing refined fitting to obtain a refined candidate circle; extracting the center coordinates of the positioning holes from the refined candidate circle; according to the circle center coordinate of the positioning hole and the butt joint state coordinate position, calculating the current time deviation; taking the minimum deviation as a target, solving an angular motion angular velocity instruction of each joint of the loading and unloading arm, driving each joint of the loading and unloading arm to adjust the pose until the deviation converges, and completing the butt joint of the flange at the tail end of the loading and unloading arm and the to-be-butt-jointed flange. The method is suitable for millimeter-level accurate butt joint and control of loading and unloading arm flanges in the dynamic marine environment, and the operation efficiency and safety in the complex environment are remarkably improved.

The invention discloses a GNSS (Global Navigation Satellite System) / INS (Inertial Navigation Satellite System) anti-deception navigation method based on ESKF (Enhanced Shift Keying Function) and dynamic window detection, which comprises the following steps of: 1, acquiring observation data of an INS and a GNSS, performing time synchronization and coordinate system unification on the observation data of the INS and the GNSS, and respectively eliminating a time error and a coordinate difference; 2, a dynamic window detection mechanism is designed, an error state dynamical model is constructed, the dynamic window detection mechanism is used for detecting whether GNSS cheating exists or not, and meanwhile the error state dynamical model can output stable navigation parameters; and 3, outputting a final high-precision navigation result according to the stable navigation parameters. According to the method, the problems of error accumulation and covariance distortion of nonlinear system model linearization are effectively solved, pollution of GNSS deception signals can be effectively inhibited, high-precision positioning and anti-deception capability are kept in complex environments (such as urban shielding and electromagnetic interference), and a navigation system with high precision and high reliability is formed.

The invention discloses an AUV (Autonomous Underwater Vehicle) path tracking method based on predicted line-of-sight angle guidance, which comprises the following steps: acquiring a real-time navigation state through inertial navigation, acoustic positioning and DVL fusion, introducing a fixed time disturbance predictor to estimate a sideslip angle and an ocean current velocity component on line, adaptively adjusting a line-of-sight distance according to transverse error-navigational speed-curvature, and tracking the path of the AUV. Calculating a predicted line-of-sight angle and outputting an expected heading; and then a propeller and a control surface are driven by adopting a fixed time feedback control law, so that track and attitude error fixed time convergence of the under-actuated AUV under the conditions of strong time-varying ocean current and large sideslip is realized. The method does not need a side thruster or an ocean current prior model, is simple in algorithm structure, is suitable for a high-speed high-curvature track, and has the advantages of high speed, high steady-state precision, low energy consumption and high robustness.

The invention discloses a vehicle-mounted laser gas pollution detection and prediction system, which comprises a mobile laser detection platform, a machine prediction system and a dynamic pollution map generation system, and is characterized in that the mobile laser detection platform is carried on a new energy vehicle and is integrated with a laser gas detector, a high-precision positioning module, an inertial navigation system and an environment sensor group; the machine prediction system receives real-time traffic flow data, weather forecast data and topographic data and outputs a pollution diffusion prediction result; the dynamic pollution map generation system comprises a space-time synchronization module, a data fusion module and a pollution event marking module. And the space-time synchronization module binds the gas pollution data with the positioning coordinates and the millisecond timestamp through hardware clock synchronization.