122 results about "Geographical maps" patented technology

Various embodiments discussed herein relate to using one or more language models and / or mapping platforms to generate a response to a natural language question or command regarding geographical information associated with a mapping platform. In response to receiving such natural language question or command, some embodiments first extract contextual data. Based at least in part on the extracting of the contextual data, various embodiments then provide the contextual data and the natural language command or question as input into one or more language models such that the one or more language models and / or mapping platforms generate a response. Some embodiments then cause presentation of an indication associated with the response.

The invention provides an online map construction method and device fusing time sequence prior and historical global map prior, and relates to the technical field of online map construction.The method comprises the steps that time sequence BEV features and online generated BEV features are efficiently fused through multi-channel cross attention based on masks; adaptively fusing the time sequence enhanced BEV features and local BEV features provided by a historical map through a spatial prior gating network; a mixed prior ROI mask is generated through prior information provided by a time sequence and a historical global map, and initialization of map query in map decoding at the current moment is assisted, so that the reliability of online map construction is improved.

The invention relates to an intelligent map making system and method based on a large language model, and the method comprises the steps: enabling a client to input data analysis information and a map making demand to a task planning Agent of a server, and carrying out the reasoning and disassembly of the input information into preliminary planning information through a double-LLM mechanism, the method comprises the following steps that Agent is used as a tool library, a tool library document, a knowledge library and a memory library are further inquired, a tool is selected through RAG and sent to a client side, if an existing tool cannot meet requirements, the Agent will generate a special code to complete a task, the client side calls the tool to carry out specific drawing according to received information, and a user can re-plan and adjust the drawing process through dialogue. The memory bank records session information and charting interaction operation information of this time and history. The problem of system fragmentation is solved through a unified architecture, stability and flexibility are balanced by combining large language model driving, tool agent and code generation, domain knowledge is introduced to enhance decision and improve specialty, and a user preference memory mechanism is constructed to realize personalized services.

Systems and methods are provided to select a set of candidate listings having geographic locations within a geographical area, fit a bound for a maps viewport to the set of candidate listings, generate a maximum score for the set of candidate listings based on a booking probability for each listing, a distance of the listing location from a center of the bound for the maps viewport, and visibility based on other listings. The systems and methods further optimize the listings shown in the maps viewport by removing and replacing farthest listings up to a predefined number of listings to be removed and computing a cumulative booking score for each set of listings to compare to the maximum score. The systems and methods cause display in a maps viewport in a user interface of a computing device of a set of listings that has a maximum score.

The invention relates to a historical image-text-based three-dimensional ancient city model construction method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining historical image-text data of a target city, the historical image-text data comprises related historical literatures of the target city in a specified period, an electronic ancient map corresponding to an ancient map drawn in the specified period, an electronic old map corresponding to an old map surveyed and mapped in the latest period from the specified period, and a shot satellite image; based on the historical image-text data, generating a city plane restored map of the target city in a specified period; extracting semantic information of the target city in a specified period from at least one kind of data in the historical image-text data, wherein the semantic information comprises city information of the target city in the specified period and attribute information of constituent elements; and generating a three-dimensional ancient city model of the target city in a specified period based on the semantic information city plane restoration map. Therefore, a high-precision and high-integrity three-dimensional ancient city model of the target city in the specified period can be constructed.

The invention relates to the technical field of historic site restoration, and discloses a historic site surrounding landscape atmosphere perception simulation and historical authenticity reconstruction method, which comprises the following steps: (S1) carrying out site region multi-dimensional data acquisition and integration; (S2) analyzing historical authenticity factors and extracting value features; (S3) constructing a landscape atmosphere perception index system and quantifying factors; (S4) performing multi-period historical scene simulation and atmosphere perception modeling; and (S5) carrying out landscape atmosphere perception simulation analysis and authenticity verification. According to the historic site surrounding landscape atmosphere perception simulation and historical authenticity reconstruction method, multi-dimensional data acquisition and integration and historical element analysis are performed, the relevance between a site and surrounding natural, artificial and humanistic environments is systematically reconstructed, and the defect that only a single building is focused in the prior art is overcome; for example, oblique photography and ancient book map fusion are utilized to restore the spatial topological relation among the ruins, historical water systems and ceremony paths, and a complete environment system supporting historical functions is formed.

The invention discloses a travel map searching system and method based on deep learning and a Beidou database, and the method comprises the following steps: obtaining the position and track data of a user, loading a geographic object, and constructing a heterogeneous map; receiving a natural language request, extracting a semantic vector and writing the semantic vector into the graph; constructing a graph comparison learning network, generating a view and executing embedded learning; optimizing structural parameters by using a pigeon inspired algorithm, and outputting an optimal model; constructing a current position node, extracting a local sub-graph, and generating a sorting list; executing path reasoning, generating a recommendation result, and feeding back and updating. According to the method, deep semantic understanding and geographical trajectory modeling are fused, so that high-precision, interpretable and self-learning travel map intelligent search recommendation under the driving of the current position of the user is realized.

The invention discloses a map construction method and system based on VLM and SLAM positioning, and relates to the technical field of map construction, and the method comprises the steps: carrying out the preprocessing of current environment data collected by a multi-modal sensor, and obtaining multi-modal target data; performing environment positioning and map construction on the multi-modal target data through an SLAM technology to obtain an initial three-dimensional environment map; when a blank area exists in the initial three-dimensional environment map, reasoning environment semantic information in the current environment data through a visual language model to obtain a semantic completion map; and fusing the semantic complemented map with the initial three-dimensional environment map to obtain a dense map. Due to the fact that the visual language model is combined with the SLAM technology, the blank area in the initial three-dimensional environment map generated by the SLAM technology can be automatically complemented through understanding and reasoning of the visual language model on the environment semantic information, and therefore the precision and robustness of map building are improved.

The invention belongs to the technical field of building identification, and particularly discloses a historical building intelligent identification method and system based on multi-source spatio-temporal data, and the method comprises the steps: building a unified spatio-temporal grid reference through collecting and fusing a historical map, a multi-temporal remote sensing image and laser radar point cloud data; three-dimensional shape and structure features and space-time semantic attribute features of the building are extracted from the fusion data set, and cross-modal feature deep fusion is performed by using a double-flow space-time neural network; and finally, completing intelligent identification and multiple verification of the historical building based on the fusion features, and outputting a structured result containing a distribution map and an attribute database. According to the method, the problems of single data dimension, dependence on artificial experience and insufficient result practicability in a traditional method are effectively solved, the full-process automation and intelligence of historical building recognition from data perception, feature analysis to result output are realized, and the recognition accuracy and efficiency are remarkably improved.

The invention belongs to the field of tourism data processing, and provides a GIS-based culture and tourism spatio-temporal feature fusion system, which comprises a data acquisition module used for acquiring culture and tourism spatio-temporal data; the data fusion module is used for establishing semantic association between the cultural tourism data based on the knowledge graph; the GIS topological structure construction module is used for constructing a topological graph of the culture and tourism data and constructing a topological relation between the culture and tourism data based on the similarity of the topological graph and the semantic association relation; the culture and tourism time-space feature fusion module is used for constructing a culture and tourism fusion map; matching the tourist trajectory data with the cultural tourism resources; determining an influence range of the cultural activity; the prediction module is used for predicting a tourist diffusion thermodynamic diagram of a preset destination in a preset time; and the visual display module is used for displaying the cultural tourism fusion map and dynamically displaying the tourist diffusion thermodynamic diagram on the cultural tourism fusion map.

The invention belongs to the technical field of laser SLAM (Simultaneous Localization and Mapping), and particularly relates to a lightweight spherical map representation method, device and equipment for point cloud data. The method comprises the following steps: dividing point cloud data into at least one local point cloud according to a preset standard; projecting the local point cloud to a unit spherical surface, sampling in a preset mode based on scene attributes of the local point cloud to generate a local spherical map, establishing a globally unique index for sampling points based on a K-dimensional tree, segmenting the local point cloud into a plurality of point cloud blocks based on the sampling points, storing the structural features of the fitting plane of the point cloud block in the local spherical map; and forming lightweight spherical map representation of the point cloud data by all the local spherical maps and the corresponding poses. The invention provides a map representation method for lightweight point cloud data.

The invention discloses a structured corpus generation method and device for geological map multi-modal large model training, and the method comprises the steps: preprocessing geological vector data, and constructing a semantic aligned geological data set; randomly selecting a data viewport, and setting the geographic space range and size of a map viewport; configuring a plurality of visual parameter items, performing controllable random adjustment on text labels, element symbols and map maps, and customizing and producing geological map samples as required; extracting multi-dimensional attribute information of the geological map sample to construct structured meta-information annotation data, and constructing a geological element mask annotation file to obtain a structured corpus for geological map multi-modal large model training. According to the method, large-scale production of the training samples with diversity, high quality and image-text alignment features is realized, the geological map corpus meets the requirements of multi-modal large model training on data scale, diversity, labeling precision and modal alignment, and the training efficiency and generalization ability of a geological map intelligent interpretation understanding model are remarkably improved.

The invention relates to the technical field of robot positioning and map construction, and particularly discloses a self-adaptive LiDAR-IMU SLAM method fusing intensity features and Riemannian manifold ground constraints, and the LiDAR-IMU SLAM method comprises the following steps: a, original measurement; b, data preprocessing; c, feature extraction; d, carrying out ground manifold constraint; e, optimizing the factor graph; and f, outputting data. The method can solve the problems that in the prior art, matching fails in a low-texture environment due to dependence on geometric features, positioning drifting is caused by point cloud distortion and inertial accumulative errors, and Z-axis errors are continuously expanded due to lack of dynamic adaptation to complex terrains. Experimental results show that according to the self-adaptive LiDAR-IMU SLAM method, the Z-axis drift error is remarkably reduced by 67.78%, the minimum absolute pose error is 0.254 m, the environment sensing and mapping capacity of the mobile robot in the complex underground space is remarkably improved, and reliable technical support is provided for intelligent inspection and infrastructure monitoring of the underground space.

The invention belongs to the technical field of maps, discloses a method and a system for improving forest environment SLAM precision by using TLS high-precision map constraint, and provides a method and a system for improving forest environment SLAM precision by using a millimeter-level point cloud map scanned by ground-based laser scanning (TLS) under a static condition as a space reference. And calculating the relative pose transformation between the PLShh scanning point cloud and the TLS point cloud as an external absolute constraint, introducing the external absolute constraint into the SLAM system by constructing a factor graph, and performing global optimization to improve the trajectory precision and map consistency. In addition, the scheme can be seamlessly fused with the existing SLAM framework, and has important significance for promoting the application of the PLShh in forestry investigation and ecological monitoring.

The invention relates to the technical field of SLAM (Simultaneous Localization and Mapping), and provides a dynamic SLAM method and system based on static semantic anchor points, comprising the steps of static structure semantic anchor point generation, anchor point-based robust tracking and multi-sensor tight coupling fusion, back-end optimization and static semantic map construction. By actively selecting high-stability static structure features and combining lightweight semantic segmentation and space-time consistency verification, the problems of poor dynamic elimination effect and high calculation overhead in the prior art are solved. According to the method, the positioning robustness and precision in a dynamic scene are improved, the calculation overhead is reduced, the static map rich in semantics is generated, and the universality is high.

The invention discloses a method for generating an intangible cultural heritage map under the assistance of artificial intelligence, and the method comprises the steps: firstly collecting non-immortal item information from a multi-source heterogeneous data source, associating a space-time tag, and extracting non-immortal gene features; associating the non-perpetual development data with the environmental data by using a knowledge extraction technology; three types of dynamic relation layers are constructed in real time by adopting natural language processing, conflict information is merged through a knowledge fusion technology, and data accuracy is guaranteed; according to the three types of entity relation layers, combining time axis slicing and GIS spatial analysis, and utilizing a sequence modeling algorithm to reconstruct a non-genetic gene cross-spatiotemporal propagation path; and finally, mapping the propagation path to a non-abandoned map, and dynamically displaying related coordinates in a highlight manner according to non-abandoned keywords input by tourists. According to the method, intelligent reconstruction and visualization of the non-genetic genetic propagation path are realized, personalized services are provided for tourists, and the method has great significance in promoting inheritance and propagation of non-genetic culture.

The invention provides a semantic map construction method, device and system for robot navigation. The method provided by the embodiment of the invention can comprise the steps of geometry-topology SLAM increment updating, sparse imaging evidence generation, analysis availability field calculation, formalized semantic constraint compiling, increment satisfiability solving and minimum conflict processing, logic entropy driven active exploration, updating change arbitration and audit account book maintenance. Wherein the increment satisfiability solving and the minimum conflict processing comprise the following steps: executing increment satisfiability solving on a formalized semantic constraint set, if the formalized semantic constraint set cannot be satisfied, positioning a minimum unsatisfiability subset, approximately determining a minimum constraint set according to a rollback set, and executing minimum rollback processing to obtain a constraint solving output result, the constraint solution output result comprises a consistency solution space generated in the current period and a logic entropy value. According to the method, accumulated errors or logic contradictions of semantic information in long-term operation can be effectively avoided, and stable evolution of the semantic map is ensured.

To provide a device and method that can provide an environment in which participants in a "space" for thinking and discussing can consider things from a wide variety of perspectives. [Solution] According to this embodiment, the map classifies fields related to society in the first direction, classifies the level of each field in the second direction (social domain in the Arctic direction), and classifies words related to individuals in the third direction (personal domain in the Antarctic direction). Multiple nodes with semantic content are placed in the social domain and the personal domain according to the words (attribute information) at their placement location.

The application belongs to the technical field of map knowledge, and particularly relates to a map knowledge representation method based on a knowledge graph. The method first acquires map data, extracts map knowledge therefrom, including concept class knowledge and rule class knowledge, the concept class knowledge being common sense knowledge in the field of cartography and including map element knowledge; the rule class knowledge being various models, rules and principles formed in the process of map making; then generates a map knowledge network graph based on the knowledge graph according to the map element knowledge; and finally performs knowledge reasoning according to the rule class knowledge, completes the map knowledge network graph, and generates new entities and / or new entity relationships. The application fully mines geographical knowledge contained in a map, provides a basis for all-round knowledge mining and fusion of the map, and has certain reference value for realizing the transformation of 'data-information-knowledge'.

This invention discloses a local SLAM construction method, a global SLAM construction method, and a construction device. In this embodiment, a cloud map and a real-time map are compared, and an object classification model is used to obtain the object classification of the current scene. Based on the object classification, prediction updates are performed, and a sub-map is obtained based on the prediction updates. The updated sub-maps obtained by the local SLAM construction method are then fused to obtain the global map. By classifying objects into dynamic and static objects, and predicting the motion of dynamic objects, a sub-map is obtained based on the prediction results, enabling real-time identification of dynamic objects.

The invention relates to the technical field of ocean space planning, in particular to an ocean function space configuration method based on landscape ecology. The method comprises the following steps: acquiring multi-source geographic space data of a target sea area, and integrating the data to generate a reference marine landscape map; calculating a group of predefined marine landscape pattern indexes according to the reference digital marine landscape map, and quantitatively evaluating the space structure of the map through the marine landscape pattern indexes; an iterative space optimization algorithm is executed, and the spatial layout of the functional area is reconstructed on the premise that constraint conditions are met by taking optimization of an ecological structure as a target; and finally, outputting a marine function space configuration diagram after ecological optimization. According to the method, the limitation of a traditional qualitative zoning method is overcome, a scientific, quantitative and repeatable process is provided for ocean space planning, and therefore the ecological integrity of ocean management planning is effectively improved.

An approach is provided for mock map data for map design validation. For example, the approach involves calculating one or more combinations of one or more map feature attributes, one or more map feature attribute values, or a combination thereof. The approach also involves creating one or more geometric features respectively for the one or more combinations. The approach further involves determining an arrangement of the one or more geometric features within a designated geographic area. The approach further involves generating mock map data based on the arrangement and providing the mock map data to a map client. The map client, for instance, renders the mock map data in a map image based on a map style taxonomy.

The present application discloses a method for recognizing architectural patterns, which is based on multiple spatial proximity graph distances and architectural attribute features, and is used to identify architectural complexes with complex nonlinear spatial distribution patterns. The present application constructs three graph sequences to capture the spatial adjacent structures and non-spatial features of different feature views, and then obtains three improved graphs through a graph diffusion process, and fuses them into a joint graph shared by all views, which can depict the mutual relationships between them and produce the final clustering results. The recognition method of the present application uses two distance metrics, contour distance and centroid distance, to make full use of the complementary information of spatial structure and non-spatial attributes, and to determine architectural patterns by combining spatial proximity relationships and non-spatial similarities, providing technical support for aspects such as map making synthesis and urban scene semantic segmentation, and representing geographical reality as realistically as possible within the limitations of map scale.

The application relates to the technical field of robots, in particular to a lightweight topological map construction method for scene recognition, which comprises the following steps: collecting data and processing the data to obtain accumulated point cloud; extracting scene descriptors; calculating the similarity between the descriptors to generate topological nodes; and calculating an optimal topological map. The application describes a scene according to multi-frame point cloud data accumulated according to a robot running track, extracts a descriptor of the point cloud, and judges whether to generate a topological node according to the similarity of the descriptor; the application can guarantee effective construction of a lightweight topological map, is particularly suitable for the demand of large-range scene topological map construction, and compared with an appearance-based topological map construction method, the number of topological map nodes constructed by the application is greatly reduced, but the reliable scene recognition performance can still be guaranteed.

Embodiments herein disclose methods for indicating a spatial map employment for a localization service. The method includes sending, by a first entity (102), a subscribe request to subscribe for a spatial map employed event to a second entity (112). The subscribe request may include a map identity, an identity associated with a requestor, and at least one security parameter. The method further includes receiving, by the first entity (102), a success response from the second entity (112) based on the subscribe request. The success response may include a subscription identity.

The application discloses a kind of based on multi-source information fusion accident disaster semantic map construction method, system and computer readable storage medium, method includes the following steps: time synchronization is carried out to multi-source data, space alignment, denoising and smoothing processing;Based on the multi-source data after pre-processing, carry out semantic feature extraction, semantic feature includes geometric feature, visual semantic feature and environmental semantic feature;Using hierarchical fusion method, first fusion geometric feature and visual semantic feature, generate preliminary fusion feature set, again secondary fusion is carried out to preliminary fusion feature set and environmental semantic feature, generate secondary fusion feature set including geometric feature, visual semantic information and environmental semantic information;With the three-dimensional point cloud geometry map constructed by synchronous positioning and mapping method as carrier, semantic label in secondary fusion feature set is mapped to the corresponding three-dimensional position of geometry map, constructs three-dimensional semantic map.The application can improve the comprehensiveness of rescue information under accident disaster environment.

A community-based nature conservation planning system for pilgrimage cities, consisting of: A data collection module gathers qualitative data from various stakeholder groups, including residents, government officials, non-governmental organizations, tourists, pilgrims and businesses, using surveys and questionnaires; a module for identifying interest groups, configured to classify interest groups based on their attributes such as power, legitimacy and urgency, and to divide the interest groups into primary, secondary and tertiary interest groups; a community mapping module configured to generate a shared cultural heritage map by aggregating data on cultural heritage sites, priority intervention areas, indicators of physical impact, indicators of economic impact, and indicators of socio-cultural impact of pilgrimage tourism; a participation assessment module configured to evaluate the level of citizen participation in urban conservation by analyzing stakeholder responses and determining the level of participation based on predefined criteria; a framework generation module consisting of a computing processor configured to generate a cyclical and iterative community-based nature conservation framework consisting of several phases, including defining objectives based on community needs and goals, analyzing information exchange, identifying appropriate forms of community participation, jointly developing nature conservation plans, and identifying intervention strategies; a data storage module configured to store the collected data, the shared cultural heritage map, the evaluation results, and the generated framework; and a user interface connected to the data storage module and configured to display conservation strategies and dissemination recommendations based on the generated framework for implementation in the pilgrimage cities.

The invention relates to a method of performing a map learning via a unified framework comprising the steps on a computing device (10): - Retrieving data comprising features that are geospatially referenced and / or localized with respect to geospatially referenced; (S1) - Arranging the features in relation to each other on the basis of their localization and / or their geospatially referenced features, whereby a lane is determined and / or aligned; (S2) - Aggregate and / or cluster geometric features; (S3) - Determine a lane divider and / or lane segments based on the geometric features and / or based on lanes traveled; (S4) - Deriving a lane topology based on a connectivity of the lane segments; (S5) and - Semantic learning based on the lane topology, whereby features are assigned a function and the map is thus created or expanded. (S6) Furthermore, the invention relates to computer program and a computing device (10).