72 results about "Real Time Kinematic" patented technology

The invention discloses a multi-mode fusion time service method and system based on dynamic calibration of DCP equipment. The method comprises the following steps: completing initial time reference data acquisition based on a multi-mode satellite signal; meanwhile, time data of a ground time service network are collected, and motion parameters of DCP equipment are monitored in real time through an inertial navigation unit; establishing a correlation model of the motion parameter and the time service error; quantitative analysis of error sources is completed based on the correlation model; fusing the multi-source time data; dynamically adjusting the fusion weight of each data source according to the real-time motion state of the DCP equipment; redundant time slots are automatically distributed to high-error equipment; outputting the calibrated time signal to DCP equipment through an interface to complete clock synchronization; and continuously monitoring the time deviation of the DCP equipment, and dynamically updating the calibration parameters to form closed-loop optimization. And the environmental adaptability and the precision stability of the timing system are improved.

The invention discloses a robot automatic navigation method and system based on depth vision fusion, and relates to the technical field of intelligent navigation, and the method comprises the steps: carrying out the registration of a point cloud subset of continuous frames through employing an ICP algorithm, distributing weights for a static obstacle and a dynamic obstacle, and carrying out the fusion, and obtaining a fused environment perception data set. The method comprises the following steps: updating a dynamic environment in real time, generating a dynamic environment map, carrying out trajectory tracking on moving targets by using binocular vision equipment, calculating a real-time motion trajectory of each moving target, obtaining an environment hotspot map, generating a global navigation path for a robot by using an A * algorithm, planning a detouring path at the periphery of a hotspot area, and outputting a navigation path sequence. According to the method, intelligent optimization of the motion path of the robot is realized through path planning and an obstacle avoidance strategy, the safety is ensured, the path efficiency is maximized, and unnecessary detour and pause time is reduced.

The invention provides an unmanned aerial vehicle recognition method, device and equipment, a medium and a computer program product, and the method comprises the steps: inputting a multi-dimensional feature vector of a to-be-detected terminal into a motion mode recognition model, and outputting a motion mode type; if the type of the motion mode shows that the to-be-detected terminal is suspected to be an unmanned aerial vehicle object, performing spatial matching on the multi-dimensional feature vector and GIS data to obtain a geographic information model; and determining whether the to-be-detected terminal is an unmanned aerial vehicle or not according to a comparison result of the real-time motion state of the to-be-detected terminal and the geographical environment characteristics. The unmanned aerial vehicle identification method provided by the invention not only considers the motion information of the to-be-detected object, but also combines GIS information, especially auxiliary verification of actual road network information and building information, can distinguish the unmanned aerial vehicle and other targets easy to confuse with the unmanned aerial vehicle in a complex environment, can realize accurate identification of the unmanned aerial vehicle, and improves the detection accuracy of the unmanned aerial vehicle. And decision accuracy is improved.

The provided is a minimally invasive puncture system based on a navigation system. The minimally invasive puncture system includes a puncture instrument and an electromagnetic navigation module. A first electromagnetic positioning sensor in the electromagnetic navigation module is fixedly provided on a puncture needle body portion of the puncture instrument, and a second electromagnetic positioning sensor is slidably sleeved on the puncture needle body portion. An electromagnetic positioning reading device in the electromagnetic navigation module is configured to acquire real-time coordinates of the first electromagnetic positioning sensor and the second electromagnetic positioning sensor, so as to obtain a real-time movement trajectory of the second electromagnetic positioning sensor relative to the first electromagnetic positioning sensor, thereby determining whether a real-time needle insertion trajectory of the puncture needle body portion entering the human body conforms to a system-default needle insertion trajectory.

The invention provides a vehicle turning path planning method and device for irregular land parcels, and is applied to the technical field of path planning, and the method comprises the steps: carrying out the initialization of a pheromone field based on the boundary data of a geographic information system and internal obstacle data, and constructing a rasterized map for representing a passable region; based on the current state of the vehicle, determining the minimum distance of obstacles in the surrounding environment of the target vehicle; based on the real-time movement speed, the minimum turning radius of the target vehicle is determined; determining a dynamic corridor parameter of the target vehicle based on the minimum distance and the minimum turning radius of the surrounding obstacle; based on the dynamic corridor parameters and the pheromone field of the rasterized map, generating a turning point probability density field of the target vehicle, and sampling the turning point probability density field to obtain a turning point set; and constructing a turning path of the target vehicle based on the turning point set, and determining the turning cost of the turning path. According to the invention, Pareto optimization of energy consumption and efficiency in a complex scene can be realized.

The invention relates to the technical field of unmanned aerial vehicle autonomous control, and discloses an unmanned aerial vehicle cluster formation control method and system based on a multi-level intelligent algorithm, and the method comprises the steps: obtaining the external environment monitoring data and motion state data of an unmanned aerial vehicle cluster, constructing a multi-target comprehensive cost function, and carrying out the optimization of a cluster formation initial track, obtaining an optimal trajectory set meeting dynamic constraints; executing collision risk assessment on the sampling points on the optimal trajectory set, and outputting a trajectory safety judgment result; performing mathematical characterization and eigenvalue modulation on the formation topological structure through a Laplacian matrix, and generating target formation parameters adapted to environmental constraints; and finally, converting the optimal track set and the target formation parameters into a bottom layer flight control instruction, driving the unmanned aerial vehicle to execute a flight action, and collecting real-time motion state data at the same time. Therefore, the problems that in the prior art, trajectory optimization convergence is slow, collision detection real-time performance is poor, formation dynamic adaptation is insufficient, and system module collaboration is weak are solved.

The invention provides a two-dimensional formation composite sliding mode control method under an explicit convergence time limit, and relates to the technical field of automatic driving cooperative control. The method comprises the following steps: firstly, acquiring real-time motion state information of a pilot vehicle and N following vehicles, and establishing a third-order nonlinear dynamic model of each following vehicle; calculating a tracking error of the following vehicle based on the virtual vehicle strategy; dynamically processing the predetermined performance constraints; constructing a composite finite time sliding mode surface of a layered structure, and determining a total execution time limit required by convergence of all monitoring signals in the two-dimensional vehicle formation control system from an initial deviation state to a predefined steady state region; and finally, on the basis of the composite finite time sliding mode surface, an external disturbance boundary is estimated online in combination with an adaptive control algorithm, a control instruction is generated, and a monitoring signal is forced to reach a steady state in an explicit time upper boundary. The method provides a visual performance estimation means for practical engineering application, and improves the stability, rapidity and accuracy of two-dimensional formation control.

The application relates to the technical field of data processing, and discloses a radar real-time data transmission processing classification identification method and system.The method comprises the following steps: performing track mode identification on narrowband data of a target radar to obtain a real-time motion mode category of the narrowband data; performing directional region selection on synchronous wideband echo data of the target radar based on the real-time motion mode category to obtain a signal segment of the synchronous wideband echo data; performing sparse decomposition on the signal segment to obtain compact features of the signal segment; performing motion mode compatibility quantification on the compact features based on the real-time motion mode category to obtain category scores of the compact features; performing feedback adjustment on the real-time motion mode category based on the category scores and the compact features to obtain an optimized motion mode of the real-time motion mode category; and performing confidence fusion judgment on the optimized motion mode to obtain a classification identification of the real-time motion mode category; and the application can improve the efficiency of radar real-time data transmission processing classification identification.

The invention discloses an RTK (Real Time Kinematic) positioning method applicable to a quadruped robot in an outdoor wide area range, and aims to solve a series of problems caused by insufficient adaptability of an existing GNSS (Global Navigation Satellite System) RTK positioning scheme to the quadruped robot. Accessing a network differential data server by using an NTRIP network protocol through a built-in 4G mobile network receiver of the GNSS receiver, and trying to obtain RTCM3.2 differential data; in the GNSS receiver, if the RTCM3.2 differential data is successfully received, RTK calculation is carried out by combining the satellite original data and the RTCM3.2 differential data, and RTK positioning data is generated; and outputting the generated positioning data to a main controller of the quadruped robot through a communication interface of the GNSS receiver.

The invention provides a multi-parameter collaborative optimization self-adaptive hydraulic PTO wave energy power generation system. The system comprises a hydraulic energy storage and release PTO unit, a hydraulic motor, a direct-current generator, a detection unit, an optimization unit and a control unit. The hydraulic energy storage and release PTO unit comprises a floater, a hydraulic cylinder and an energy storage unit, the energy storage unit comprises two energy accumulators, and a hydraulic motor drives a direct-current generator to generate power by using pressure potential energy released by the energy accumulators; the detection unit is used for acquiring real-time motion data of the floater and real-time pressure data of the energy accumulator; the optimization unit uses the power-stability combined optimal target function to search and obtain the optimal value of the multi-parameter combination of the wave energy power generation system, and the control unit adjusts the displacement of the hydraulic motor and the load resistance of the direct-current generator based on the optimal value of the multi-parameter combination and switches the energy storage and release processes of each energy accumulator. The power generation system provided by the invention can adaptively realize the optimal output of the generated power while ensuring the stability of power generation.

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

The utility model discloses a blind guiding device which comprises a stick head arranged at the top of a stick body, a handle arranged on one side of the stick head and used for being supported by a user, a moving module arranged at the bottom of the stick body, a positioning module arranged in the stick head, an inertia measurement module and a data processing module arranged in the stick body, and a data processing module arranged in the stick body. The power module, the camera and the laser radar are arranged on the outer side face of the stick body, the camera and the laser radar are arranged at the positions, close to the stick head, of the stick body and are arranged in the direction opposite to the extending direction of the handle, and the data processing module is used for conducting SLAM mapping and obstacle information detection. The navigation module is used for receiving the SLAM mapping result and generating navigation data capable of avoiding obstacles based on the SLAM mapping result and the obstacle information, and the moving module is used for receiving the navigation data and moving according to the navigation data. By the adoption of the embodiment, real-time movement in a complex environment can be achieved, the blind person can go out only by following traction walking of the blind guiding device, and the going-out efficiency of the blind person is improved.

The embodiment of the invention relates to the technical field of computers, and discloses a vehicle-mounted information display method, device and equipment and a storage medium, and the method comprises the following steps: obtaining real-time motion parameters and navigation data of a vehicle; on a navigation path in the navigation data, displaying lyrics of the played song in a rolling manner according to display parameters; wherein the display parameters are related to the real-time motion parameters and the navigation data. By applying the technical scheme of the invention, the driving experience can be improved, the entertainment can be increased, and the driving safety can be enhanced.

The utility model discloses an RTK (Real Time Kinematic) measuring rod with a fan-shaped tip, which belongs to the technical field of surveying and mapping instruments and can solve the problem of low measuring precision when the existing RTK measuring rod is used for measuring loose soil such as soft cultivated land, desert or sludge. The measuring rod comprises a single rod; the fan-shaped tip is connected to the bottom end of the single rod; the fan-shaped tip comprises an inverted cone part and a fan-shaped part; the bottom surface of the fan-shaped body part is fan-shaped, and the height of the fan-shaped body part is the same as that of the inverted cone part; the vertex of the fan-shaped body part is located on the central axis of the single rod and coincides with the vertex of the inverted cone part. The utility model is used for the RTK measuring rod.

This invention discloses an intelligent object-finding and positioning method and system based on UWB and IMU fusion. The positioning method includes the following steps: S1, acquiring UWB positioning signals to obtain the reference position and distance data of the target object, and collecting IMU three-axis acceleration and three-axis angular velocity data through a mobile terminal, and constructing a UWB and IMU fusion dataset after filtering; S2, using the trapezoidal integral method to perform a second integration of the acceleration to obtain displacement data, and combining gyroscope angle compensation to correct the motion heading, outputting a real-time motion coordinate sequence; S3, using the last effective UWB sensing position as the starting point, combining motion coordinates, UWB distance constraints, and gyroscope angle constraints to generate multiple sets of candidate lost positions; S4, using the least squares method to fit and optimize the candidate positions, and outputting the optimal lost coordinates. The above positioning method constructs a positioning dataset by fusing UWB and IMU data, realizing continuous and accurate positioning of target objects in scenarios where UWB signals are lost or abnormal, and improving the positioning accuracy of intelligent object finding.

The invention provides a surface clutter real-time generation method and device, and the method comprises the steps: determining a target time domain range and a target frequency domain range of a to-be-generated surface clutter signal according to the real-time motion state parameter of a carrier carrying a radar seeker and the beam pointing parameter of the radar seeker; generating a random clutter sequence covering the target time domain range and the target frequency domain range according to a preset amplitude statistical distribution model and a preset power spectrum model; a surface clutter signal is generated by modulating a reference radar signal, the modulation including convolving the reference radar signal using a random clutter sequence, and parameter adjusting the convolved signal to match dynamic characteristics of a carrier. According to the invention, the problem of insufficient fidelity of clutter simulation signals in the prior art is solved.

The invention discloses a control system and method for synchronous coupling of a robot motion state and an acousto-optic warning time domain, relates to a man-machine interaction technology, and provides a scheme for solving the problems of motion state and acousto-optic separation and the like in the prior art. When the host receives a moving or grabbing task, the multi-mode synchronous planner generates a mechanical arm joint space trajectory, and meanwhile real-time kinematics feature vectors of the end effector in a Cartesian space are calculated in parallel; converting the physical motion parameters into target warning efficiency parameters according to a preset nonlinear model, and sending the target warning efficiency parameters to the intelligent warning terminal; the intelligent warning terminal directly sends real-time lighting effect data to the PID and aging compensation controller; sending the state switching instruction to a stack type finite-state machine for logic processing; and a hardware feedback signal is combined to form closed-loop control, and finally the LED array and the buzzer are driven to send out an acousto-optic signal which is strictly synchronous with the action of the robot. The device has the advantages that the warning lamp changes along with the speed of the mechanical arm, and the frequency of the buzzer changes suddenly along with acceleration.

This invention discloses a method, device, electronic device, and storage medium for guiding blind people. The method includes acquiring three-dimensional point cloud data, image data, and pose data of the current environment in which the guiding robot is located; determining target detection information of a target object in the current environment based on the three-dimensional point cloud data and image data, including the distance and direction of the target object relative to the guiding robot, and the type identification result of the target object; performing point cloud registration and pose optimization processing on the three-dimensional point cloud data and pose data to obtain the optimized target position and target pose at the current moment; thereby enabling path planning for the guiding robot at the current moment based on the target detection information, type identification result, target position, and target pose, so as to control the guiding robot to move according to the planned navigation data, complete the real-time movement of the guiding robot in complex environments, and improve the travel efficiency of blind people.

A predictive dynamic alarm, control, and management system is configured to simultaneously detect multiple moving and stationary entities in an environment. The system can use a combination of radio frequency ranging and local sensors to predict the expected paths of environmental entities and support motion and location data in areas with low radio frequency bandwidth.

The invention relates to the technical field of intelligent anti-swing control of unmanned aerial vehicle hoisting, in particular to an industrial internet-based intelligent anti-swing control system for unmanned aerial vehicle hoisting. Comprising a multi-source dynamics data acquisition unit used for acquiring environmental dynamics prediction data of a predetermined flight path of an unmanned aerial vehicle from a cloud platform and acquiring real-time motion state data of the unmanned aerial vehicle from airborne equipment; the prospective stability evaluation unit is used for obtaining the predicted maximum swing angle of the load; the prospective stability evaluation unit is also used for comparing and analyzing the predicted maximum swing angle and a preset load maximum allowable swing angle to obtain a prospective stability index; the control parameter adjusting unit is used for judging whether the prospective stability index is greater than a preset stability threshold value or not; and finally, the system performs active correction control on the unmanned aerial vehicle according to the corrected controller gain. According to the system, the problem of control lag is solved, so that the safety and stability of unmanned aerial vehicle hoisting operation are greatly improved under complex meteorological conditions.

Disclosed herein is a Real Time Kinematics (RTK) brokering system for distributing RTK positioning data to one or more vehicles, comprising an RTK server adapted to receive positioning data of a plurality of vehicles, dynamically define, based on the positioning data, a plurality of dynamically defined zones each associated with a respective group of vehicles located within borders of the respective dynamically defined zone and contained within a coverage area of one or more RTK base stations, receive RTK positioning correction data relating to each dynamically defined zone from one or more of the RTK base stations covering the respective dynamically defined zone, and distribute the RTK positioning correction data relating to each dynamically defined zone to the respective group of vehicles associated with the respective dynamically defined zone. Wherein one or more of the vehicles computes its location with improved accuracy based on the related RTK positioning correction data.

The present application relates to the technical field of offshore wind power cable monitoring, and discloses a method and system for risk early warning of suspended sea cable based on real-time motion state. The method comprises: arranging a sensor array on a target sea cable suspended section to collect motion data in real time; constructing a rotation matrix based on an attitude angle, filtering out the gravity component in acceleration through coordinate transformation to obtain pure motion acceleration; integrating the motion acceleration in time domain to calculate displacement, and simultaneously fusing angular velocity and attitude angle to reconstruct the three-dimensional spatial form of the sea cable, and extract the swing amplitude and bending degree; comparing the swing amplitude and the safety threshold, and the bending degree and the safety threshold in real time, generating an early warning signal according to the early warning rules based on the comparison result; triggering an audible and light alarm based on the early warning signal and generating an operation and maintenance instruction. The complete monitoring link from data collection to active intervention is realized, the reliability of monitoring is greatly improved, a double-threshold early warning mechanism is established, a closed-loop control is formed, and a high-reliability and low-cost suspended sea cable risk prevention and control system is constructed.

The invention relates to the technical field of high-altitude operation monitoring, and discloses a high-altitude operation anti-falling safety monitoring method based on data processing. The method comprises the steps of obtaining an environmental parameter set of a target operation area, and performing matching query in a historical accident database to determine a historical falling accident feature set; performing risk grade division on the falling accident feature set to obtain a plurality of graded historical falling accident feature sets, and traversing and extracting an environmental risk factor reference value and a risk influence range parameter; taking the risk influence range parameter as a boundary condition of a dynamic monitoring window, and performing multi-dimensional feature capture on the real-time motion data sequence of the high-altitude operation personnel by utilizing a plurality of configured dynamic monitoring windows to obtain a plurality of real-time motion feature sets; and carrying out space-time correlation fusion on the plurality of real-time motion feature sets to obtain a target space-time fusion motion feature set, and taking the target space-time fusion motion feature set as an anti-falling safety monitoring result. According to the method, environment and motion data are fused, and a precise monitoring basis is provided for high-altitude operation falling prevention.

The present application relates to the field of machine learning, in particular to an interference and trajectory learning method based on an integrated neural network, comprising the following steps: (1) multi-source input data preprocessing in a cooperative scenario: for the task of unmanned aerial vehicle and robot dog cooperation, collect camera depth image, real-time motion state data and cooperative task expected motion target data carried by each platform in the simulator; denoise and feature extraction preprocessing are performed on the visual data, and standardization processing is performed on the motion state and expected target data; (2) integrated neural network construction and training optimization: an end-to-end integrated neural network is constructed, the network input is the preprocessed multi-source data, and the output is the expected running trajectory of each platform and the prediction result of external time-varying interference. The present application saves the mapping link and multi-module connection step in the traditional method through the end-to-end architecture, greatly saves the calculation time, and simultaneously realizes the cooperative optimization of "trajectory planning-interference prediction".

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.

The invention provides a mobile navigation method of a hydraulic gate wall-climbing robot navigation system. The mobile navigation method comprises the steps of multi-mode sensing and data synchronization. Environment modeling and attachable area segmentation are carried out; real-time motion planning based on SBMPO is carried out; carrying out metamorphic configuration optimization and gait selection; performing layered execution and discrete state feedback control; through the SBMPO algorithm based on sampling and in combination with direction self-adaptive heuristic search, the problems that a traditional path planning method is low in efficiency and difficult to meet dynamic motion constraints in a complex motion environment are solved, meanwhile, on one hand, the problems of autonomous navigation and accurate positioning of the multi-legged robot on a vertical large-range complex surface are solved, and on the other hand, the multi-legged robot can be accurately positioned. And on the other hand, by optimizing the motion path and gait decision, mechanical loss and operation energy consumption are reduced, and the automation level and operation and maintenance safety of hydraulic steel gate detection are improved.

The application discloses a kind of multi-mode fusion time service method and system based on DCP equipment dynamic calibration, method includes: based on multi-mode satellite signal completes initial time reference data acquisition;While completing the acquisition of time data of ground time service network and the real-time monitoring of motion parameter of DCP equipment by inertial navigation unit;Establish the correlation model of motion parameter and time service error;And based on correlation model, complete error source quantitative analysis;Multi-source time data are fused;According to the real-time motion state of DCP equipment, dynamically adjust the fusion weight of each data source;And automatically allocate redundant time slot to high error equipment;Calibrated time signal is output to DCP equipment through interface, completes clock synchronization;Continuously monitor the time deviation of DCP equipment, dynamically update calibration parameter, form closed loop optimization.Improve the environmental adaptability and precision stability of time service system.

The invention relates to a time sequence RTK / INS (Real Time Kinematic / Inertial Navigation System) integrated navigation method based on double differences between GNSS epochs, and belongs to the technical field of navigation positioning and integrated navigation. The method comprises the following steps: performing single-point positioning and error correction on GNSS original observation data, and constructing an inter-epoch double-difference observation value; carrying out Lie group / manifold space pre-integration on IMU data, estimating a carrier state and assisting cycle slip detection; and finally, based on a factor graph optimization framework, fusing various constraint factors for modeling and solving, checking fixed integer ambiguity through an LAMBDA method and Ratio, and performing feedback optimization. According to the invention, centimeter-level high-precision relative positioning can be realized, and the continuity, robustness and calculation precision of positioning in a complex environment can be improved.

The invention belongs to the field of unmanned aerial vehicle motion planning, and relates to a motion planning method and device suitable for a bidirectional thrust quadrotor, and a storage medium, and the method comprises the steps: collecting the position and angle of a target point, determining the state of a vehicle body and a control quantity output constraint, and dividing the whole process into at least one flight stage; constructing a state space differential equation and a time optimal objective function, and inputting the state space differential equation and the time optimal objective function into a nonlinear solving toolbox to solve an expected value; substituting the real-time motion state data into the body kinetic model to calculate a real-time value, subtracting the real-time value from an expected value to obtain a control correction amount, and converting the control correction amount into a motor rotating speed instruction; subtracting the real-time position and attitude angle from an expected value to obtain an expected position and attitude correction; and subtracting the actual position and the attitude change quantity at the next moment from the expected position and the attitude correction quantity to obtain a deviation. And if the deviation is smaller than the preset tolerance in each control period, continuing, otherwise, adjusting the control quantity output constraint and re-planning. The method is high in adaptability, and the task execution precision and reliability are improved.