18 results about "Chart datum" patented technology

The invention discloses an automatic obstacle avoidance method and system for an unmanned ship based on Beidou artificial intelligence, and relates to the field of computer vision, and the method comprises the steps: collecting a visible light image and a near-infrared image of a water surface environment, and carrying out the reflection suppression processing; performing feature fusion on the image to generate an environment perception graph; obstacle features are extracted through a cascade cavity convolution structure, and an obstacle pixel-level semantic segmentation result is obtained; constructing an obstacle motion prediction model, and obtaining a predicted obstacle motion track; acquiring motion track data of the unmanned ship based on Beidou positioning and electronic chart data; establishing a space-time collision detection model, calculating collision parameters, and generating a collision data set; an obstacle avoidance path is generated through a dynamic situation field method, and a rudder angle instruction and a propeller rotating speed instruction are obtained. The unmanned ship has the advantages that accurate sensing, motion prediction and intelligent obstacle avoidance of the unmanned ship on water surface obstacles are realized through Beidou positioning and technology, and the sailing safety and intelligent level are improved.

The invention discloses an automatic verification method and system for a topological relation of ocean charting data, and relates to the technical field of charting verification, and the method comprises the steps: obtaining a chart vector element, splitting a broken line into a line segment unit according to a node, splitting a surface domain into a ring domain unit according to an outer ring and an inner hole, and extracting a control point; constructing fractal spectrums for the line segment units based on a multi-resolution box dimension method, comparing the fractal spectrums with normal spectrums, and marking complexity abnormal sections; constructing a polymorphic behavior matrix according to predefined geometric expectation and semantic rules, analyzing conflicts, and identifying topology anomalies; a tide level field is obtained, a coupling constraint field is constructed in combination with equal-depth closed loop hierarchical nesting, and tide depth coupling abnormity of a channel boundary and a closed loop is verified; a lighthouse, a navigation mark and a tide level station control point are screened, and connectivity abnormity is verified according to a semantic rule; and summarizing to generate a verification report. Fractal analysis, a semantic matrix, isodepth coupling and a communication rule are combined, break point errors are accurately distinguished, topological anomaly is detected in a fusion mode, and the time-space consistency of a sea chart and the connectivity of control points are guaranteed.

The invention relates to a multi-modal dynamic region chart generation loading and self-adaptive navigation method and system. The method comprises the following steps: acquiring multi-modal data information; generating a self-adaptive chart based on the static chart data and the dynamic environment information; based on the ship characteristic data and the navigation plan information, generating multi-target path information associated with a self-adaptive sea chart, and sending the multi-target path information to a ship end and a base shore end; when target path information fed back by the ship end and the base shore end is received, navigation information is generated based on the target path information; receiving feedback information from the ship end and the base shore end based on a preset receiving frequency, and updating navigation information; by integrating the static chart data, the dynamic environment information, the ship characteristic data and the navigation plan information, the navigation system with environment perception, path planning and closed-loop updating is constructed, the conversion from the static chart to dynamic adaptive navigation is realized, and the effect of improving the navigation safety and efficiency is achieved.

The application provides an electronic chart system, method and equipment with water depth change prediction capability, relates to the technical field of marine electronic information technology and marine geographic information, and the system comprises a data acquisition module, a water depth change analysis and prediction module and a risk visualization module. The application superimposes and displays predictive water depth risk information in a standard ECDIS interface through the fusion of official electronic chart data and a dynamic water depth model, so that the existing operation process of the driver can be changed, and enhanced navigation support reflecting the recent seabed change trend can be provided in the case that the chart updating cycle is long.

A steering assist system for a marine vessel has a steering control unit for receiving an operator steering command via a steering device. The steering control unit is configured to provide feedback to an operator via the steering device in response to a control signal and a positioning system configured to determine a location of the marine vessel. The system has a processing circuitry to store sea-chart data indicating one or more hazardous location areas. The system is configured to determine whether the location of the marine vessel in relation to the one or more hazardous location areas satisfies a predetermined hazard criterion, and in accordance with a determination that the hazard criterion is satisfied, transmit a control signal to the steering control unit. The steering control unit is, upon receipt of the control signal, configured to provide feedback to an operator via the steering device.

The invention relates to the field of meteorological data fusion, in particular to a man-machine collaborative ocean vessel route planning method and system combined with meteorological data, and the method comprises the steps: obtaining historical vessel navigation trajectory data and electronic chart data in response to a route planning request, and generating a global navigation grid covering a navigation area based on the data; generating an initial route from a starting point to a terminal point based on the global navigation grid in combination with preset ship parameters; acquiring weather forecast data, and coupling the weather forecast data with the initial route to deduce a future ship position of a ship on the initial route; based on the deduced initial route, receiving an editing operation of a user on the deduced initial route in real time, and forming an optimized route based on an operation result; according to the weather forecast data, calculating a comprehensive navigation performance index of an optimized route; and outputting the optimized route and the corresponding comprehensive navigation performance index based on the calculation result.

The invention discloses an algorithm and system for autonomous navigation of a Beidou navigation unmanned ship based on a flowing water area, and relates to the field of real-time positioning, and the algorithm comprises the steps: constructing a three-dimensional environment model through fusing sea chart data and depth finder real-time scanning, and obtaining high-precision position information through combining Beidou differential positioning; collecting dynamic environment data through a multi-sensor array, predicting an obstacle track by using a graph neural network, and updating the model; hull attitude, propulsion and steering engine data are monitored in real time, and the sailing state is judged in combination with historical data; an improved A * algorithm is adopted to dynamically plan a route, a control instruction is generated, and emergency obstacle avoidance is triggered; receiving a remote instruction or feeding back a risk through satellite communication; evaluating the performance after navigation, and optimizing an environment model and algorithm parameters. The method has the advantages that high-precision positioning is achieved through Beidou difference, the obstacle trajectory is predicted through the graph neural network, the route is planned through the improved A * algorithm, and the safety and the intelligent level of autonomous navigation of the unmanned ship in the flowing water area are improved.

The application discloses a kind of based on AI and ship AIS big data offshore traffic safety analysis method, belong to offshore wind farm and offshore mariculture area siting technical field, specifically include: obtaining the ship AIS data of target sea area generation ship AIS traffic flow analysis diagram;Target sea area is divided into analysis grid unit and the external navigation risk score of each grid unit is calculated;Based on risk score screening and aggregation generate several candidate site area, extract site boundary parameter;Determine the candidate mother port corresponding to each candidate site area, based on electronic chart data planning each mother port to site operation and maintenance route, calculate navigation difficulty coefficient and select minimum value as operation and maintenance path conflict index;The external navigation risk score and operation and maintenance path conflict index are weighted and summed to obtain comprehensive score, select the lowest site area as target site area as score.The application includes external navigation risk and operation and maintenance path safety into unified decision framework, realizes the multidimensional collaborative optimization of wind farm siting.

The application relates to a kind of ocean ship dynamic area loading electronic chart based on navigation path method, comprising: obtaining the starting point and the terminal point of ship voyage, generating navigation path and the whole navigation area chart data range;The sea area in the calibration area on both sides of the path is defined as the width range of target loading area;According to the current position, dynamically adjust the target loading area, request the server to download, load new target loading area chart data, and unload the chart data of the area that has passed.When the network is interrupted, the background cache chart data is used, when the cache chart data is loaded to the boundary amount, the chart cell data is extracted from each involved class file according to the geographical position of the target loading area, the subsequent chart data loading is carried out, and until the network is restored, the server chart data and the chart update compressed data of the part of the navigation area are continuously downloaded.The application can effectively reduce the rendering pressure of electronic chart software, improve the system operation efficiency and response speed.

The application relates to an unmanned ship path planning method based on an improved GA-PSO optimization, which comprises the following steps: acquiring real sea chart data, performing environment modeling and coordinate conversion according to the real sea chart data, and acquiring a planning map; constructing a multi-index comprehensive evaluation function according to the planning map; adopting an improved GA-PSO hybrid optimization method to optimize the track planning of the unmanned ship according to the multi-index comprehensive evaluation function, and acquiring the best path of the unmanned ship, wherein a path constraint detection mechanism is introduced in the optimization process, and the improved GA-PSO hybrid optimization method introduces an adaptive parameter adjustment mechanism in the traditional GA-PSO method. The application can generate a safer, smoother and implementable track of the unmanned ship, and improves the autonomous navigation capability in a complex sea area.

The invention provides a ship route planning method based on fusion of an electronic chart and dynamic meteorological information. The method comprises the following steps: determining a planned sea area range according to a ship route planning starting point and a ship route planning ending point, preprocessing navigation objects in the planned sea area based on electronic chart data, and constructing a static high-precision navigation environment model without geometric redundancy; converting the preprocessed electronic chart data into a unified plane projection coordinate system, and generating a static grid map for route planning; acquiring meteorological information data of a corresponding moment based on a planning time starting point, performing interpolation processing on meteorological information, fusing the meteorological information with the static grid map, and constructing a dynamic meteorological grid map changing along with time; and on the basis of the static grid map and the dynamic meteorological grid map, constructing a multi-level grid environment model, and performing route planning based on an improved path search algorithm to obtain an optimal route meeting ship navigation safety constraints.

The invention discloses a method and a system for dynamically supplementing an electronic chart by using shipborne sonar data. The method comprises the following steps: carrying out unified time service on sonar setting and ECDIS; collecting water depth data associated with the timestamp; the water depth data and the position data are aligned through position data interpolation; performing dynamic point-like supplement: performing center positioning according to the ship position, filtering water depth data in a certain range in the center, and displaying the water depth in a point-like supplement layer; automatic blanking: carrying out linear blanking after a set time is exceeded; alarm monitoring is carried out in real time, and when the detected water depth is inconsistent with the chart water depth, an alarm is given in time; and the detected water depth data are shared. According to the invention, shipborne sonar data and an electronic chart are combined, water depth information is obtained in a second level in a navigation process, and water depth change in a navigation channel or a navigation direction is reflected in real time, so that navigation safety and real-time performance of underwater topography reference are improved, and the problems that updating of existing ECDIS chart data is lagged and real-time water depth change cannot be reflected are solved.

The invention discloses a marine traffic transportation safety analysis method based on AI and ship AIS big data, and belongs to the technical field of offshore wind power plant and sea culture area site selection, and the method specifically comprises the steps: obtaining ship AIS data of a target sea area, and generating a ship AIS traffic flow analysis chart; dividing the target sea area into analysis grid units and calculating an external navigation risk score of each grid unit; screening and aggregating to generate a plurality of candidate site areas based on the risk scores, and extracting site boundary parameters; determining a candidate mother port corresponding to each candidate site area, planning an operation and maintenance route from each mother port to the site based on the electronic chart data, calculating a navigation difficulty coefficient, and selecting a minimum value as an operation and maintenance path conflict index; and performing weighted summation on the external navigation risk score and the operation and maintenance path conflict index to obtain a comprehensive score, and selecting the site area with the lowest score as a target site area. According to the method, external navigation risks and operation and maintenance path safety are incorporated into a unified decision framework, and multi-dimensional collaborative optimization of wind power plant site selection is realized.

This invention provides a ship path planning method and system based on Q-Learning, belonging to the field of ship path planning technology. The method includes: acquiring nautical chart data and converting it into a two-dimensional raster map; generating a grayscale heatmap of the obstacle region based on obstacle point data using a Gaussian distribution function to quantify the risk gradient; constructing a Q-Learning algorithm environment, designing a reward function that includes heatmap weights, and iteratively training the Q-table to converge and generate an initial path; acquiring historical navigation trajectory data and performing multinomial fitting; fine-tuning and optimizing the converged Q-table using the smooth trajectory features after fitting, and finally outputting a safe path that conforms to navigation habits. This invention solves the problems of single risk modeling and lack of prior knowledge utilization in traditional methods by using a dual mechanism of heatmap risk perception and historical experience transfer, achieving an organic integration of reinforcement learning autonomous exploration and human navigation experience.

This invention discloses a verifiable cryptographic fusion method for electronic nautical charts and satellite imagery, belonging to the field of marine data processing technology. The method includes: preprocessing and registering S-57 electronic nautical chart data and satellite imagery data; constructing a dynamic tidal buffer analysis region; generating a nearshore waters mask with semantic consistency; constructing Merkle tree commitments for the purified electronic nautical chart features and water index raster; extracting nearshore boundaries and calculating geometric consistency scores; calculating semantic consistency scores based on the nearshore waters mask and depth region reference maps; and finally, weighted fusion of geometric, semantic, and commitment scores to generate a reliable fusion index, which is then classified and evaluated according to a threshold. This invention combines geometric consistency, semantic consistency, and cryptographic integrity verification, enabling quantifiable and verifiable evaluation of the fusion results of multi-source marine geospatial data, providing a standardized technical path for hydrological quality assurance and chart updates.

The invention discloses a hydrothermal zone AUV trajectory planning and optimization method based on an improved myxomycete algorithm, and the method comprises the following steps: S1, global trajectory planning: carrying out the following operations through an AUV water surface monitoring station: S1, 1, setting the latitude and longitude information of an AUV navigation range based on topographic information or sea chart data; the method comprises the following steps: S1, 2, loading a navigation area chart and carrying out gridding data processing; s1, 3, loading an obstacle model and setting grid attributes according to the boundary dimension and the distribution condition of the fixed obstacle; s1, 4, constructing a preliminary trajectory node based on artificial experience; according to the method, the planning efficiency is high: by improving the myxin algorithm (chaos initialization and Cauchy variation), while the trajectory quality is ensured, the number of planning nodes is remarkably reduced, and the generation speed of the global trajectory is greatly improved; and the collision avoidance capability is strong: local planning is fused with an improved artificial potential field method and a virtual point guide mechanism, so that sudden obstacles can be effectively avoided, local extreme values can be eliminated, and the safety and reliability of navigation in a complex environment can be ensured.

The invention relates to a multi-mode fusion dynamic route planning and real-time optimization method and system, and relates to the technical field of route planning, and the method comprises the steps: obtaining real-time ship information; disassembling the real-time ship information to obtain ship dynamic data, an initial route and a real-time ship position; searching corresponding sea chart data according to the real-time ship position; obtaining a real-time route segment and a route segment end point through the sea chart data and the initial route; obtaining an ecological region corresponding to the real-time route segment; determining a preliminary optimized route according to the real-time ship position and the route segment end point, wherein the preliminary optimized route does not include the route segment end point; and obtaining an optimized route according to the ecological region and the preliminary optimized route. The method has the effect of improving the reliability and safety of route planning.

This invention relates to an automatic conversion method for S-57 and S-101 electronic nautical chart data, belonging to the field of marine surveying technology. The method involves reading and parsing S-57 nautical chart data, initializing a conversion rule engine, converting topological geometric units in S-57 into geometric simplexes in S-101, converting S-57 landmarks and their attributes into S-101 features and their attributes according to conversion rules, and handling special cases such as multi-valued attributes, tidal current tables, surrounding depths, complex features, and light arc merging; converting S-57 metadata into S-101 metadata; and finally exporting S-101 data in a preset order. This invention, by constructing a comprehensive conversion rule engine, supports the conversion of complex features and attributes, overcoming the shortcomings of existing conversion tools in terms of information completeness, accuracy, and applicability, significantly improving conversion efficiency and accuracy. It has already been applied in the chart production sector in my country.