54 results about "Real time mapping" patented technology

The invention belongs to the technical field of data processing, and particularly discloses a dynamic path planning method and system for an inspection robot, and the method comprises the steps: collecting field data through a sensor, processing a laser scanning point cloud and a camera image through a positioning mapping algorithm, and fusing multi-source information to generate a real-time map. Obtaining a three-dimensional environment model containing a dynamic obstacle position; according to the three-dimensional environment model, obstacle features are extracted, a deep learning model is adopted to identify moving personnel and randomly placed goods, obstacle types and movement tracks are judged, and a classified obstacle data set is obtained; through the classified obstacle data set, the distance and the relative speed between the obstacle and the current position of the robot are calculated, and if the distance is smaller than a preset threshold value and the speed is larger than zero, high-priority interference is marked; according to the invention, the problem of inaccurate dynamic obstacle identification and obstacle avoidance in a complex scene in the prior art is solved.

The invention discloses an unmanned aerial vehicle routing inspection path planning method and system for a power grid line, and particularly relates to the technical field of power grid routing inspection, and the method comprises the steps: 1, dynamically fusing a multi-source sensor and prior data, and constructing and updating a comprehensive threat field with a time attenuation mechanism and a passability map in real time; 2, decomposing an inspection line into subtask sections, and generating a reference route of each section by combining static safety cost; 3, on the basis of a real-time map in the flight of the unmanned aerial vehicle, a local optimal track is solved online through rolling window optimization of adaptive weight adjustment; and step 4, realizing multi-machine collaboration and automatic handover of blocked tasks through a block chain type distributed task state account book and an intelligent contract rule. According to the invention, the real-time avoidance capability, the environmental adaptability and the task continuity of the unmanned aerial vehicle to dynamic obstacles are remarkably enhanced, and the safety and the efficiency of power grid inspection operation are effectively guaranteed.

The invention belongs to the technical field of data processing, and particularly discloses an intelligent path planning and control system for an automatic driving carrying robot, and the system is operated through the following method: collecting environment data through a multi-mode sensor, and processing a laser radar point cloud and a camera image; fusing multi-source information to generate a real-time map, and obtaining a three-dimensional environment model containing dynamic obstacle positions; according to the three-dimensional environment model, obstacle features are extracted, an improved neural network model is adopted to identify a plurality of current obstacles, obstacle types and movement tracks are judged, and a classified obstacle data set is obtained; through the classified obstacle data set, the distance and the relative speed between the obstacle and the current position of the robot are calculated, and if the distance is smaller than a preset threshold value and the speed is larger than zero, high-priority interference is marked; the objective of the invention is to solve the problem that accurate sensing, real-time decision making and efficient obstacle avoidance are difficult to realize in a complex dynamic environment in the prior art.

The application provides an underground inspection path planning method for an inspection robot, and relates to the technical field of robot path planning.The method comprises the following steps: acquiring basic map data, robot basic data and an inspection plan; acquiring real-time map data and robot real-time data; determining an inspection node; determining a selectable inspection path; determining an inspection consumption coefficient; determining a preset inspection path according to the robot basic data, the real-time map data, the inspection consumption coefficient and the basic map data; determining whether the preset inspection path needs to be changed according to the basic map data, the robot basic data and the robot real-time data; in the case that it is determined that the preset inspection path needs to be changed, determining a changed inspection path according to the robot basic data, the basic map data and the robot real-time data, and performing inspection according to the changed inspection path. According to the application, the rationality of underground inspection path planning can be improved.

The invention discloses a port operation vehicle scheduling method and system based on map data, and particularly relates to the technical field of scheduling optimization. Real-time map state information of a port channel network is generated by collecting real-time map data of the port channel network and analyzing the real-time occupation state of a port channel road section. And analyzing the local change trend of the occupation state of the port channel road section and the priority change of the vehicle task based on the real-time map state information, outputting dynamically updated vehicle task priority information and local area map data updating information, identifying a priority propagation abnormal area, and generating priority inversion risk early warning information. By identifying the vehicle path conflict points causing the traffic jam, generating the path conflict resolution strategy information, adjusting the vehicle path planning and executing the vehicle scheduling, the collaboration, responsiveness and traffic efficiency of the operation vehicle scheduling in the port environment are effectively improved.

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 belongs to the technical field of unmanned aerial vehicle path planning, and particularly relates to a limited space unmanned aerial vehicle autonomous homeward voyage method based on real-time mapping and path evaluation. The method comprises the steps that when the unmanned aerial vehicle flies in a limited space without a GPS, real-time positioning is carried out through a laser radar SLAM technology, a three-dimensional grid map is constructed synchronously, and meanwhile a flight path is recorded in real time in a key point mode. When the electric quantity is insufficient or communication is lost to trigger return flight, the system generates two candidate paths in parallel, one path is a historical path which is backtracked in a reverse order, and the other path is a new path which is searched on a real-time map by using an A * algorithm. Then, the two paths are evaluated through a comprehensive scoring function, and scoring standards comprise path smoothness, path safety and path length; and finally, selecting a path with a relatively high score as an execution path, and performing safe return by combining a local obstacle avoidance algorithm. According to the invention, the limitation of pure path backtracking is overcome, and safer, more efficient and more intelligent autonomous homeward voyage is realized.

Systems and methods for real-time map data coverage optimization are disclosed. A system includes one or more processors configured to determine a real-time map data collection coverage in an interested region, wherein real-time map data are collected by one or more consumer vehicles at locations of the consumer vehicles, determine whether one or more uncovered locations in the interested region are not covered by the locations of the one or more consumer vehicles, in response to determining that the one or more uncovered locations in the interested region are not covered by the locations of the one or more consumer vehicles, generate a route comprising the one or more uncovered locations based on a map of the interested region, and send an instruction to cause operation of a data-collecting vehicle to follow the route for real-time map data collection.

The invention relates to the technical field of robot navigation and obstacle avoidance, in particular to a method for efficiently generating an Euclidean symbol distance field (ESDF) map based on laser radar point cloud clustering. Firstly, down-sampling processing and ground segmentation elimination are carried out on an original point cloud; extracting and combining obstacle point cloud clusters by adopting an Euclidean clustering algorithm, and eliminating dynamic objects at the same time; then, a sparse voxel hash table is initialized according to a set voxel resolution, and obstacle point cloud mapping is marked as occupied voxels; and finally, locally updating the distance value of the newly occupied voxels or the state-changed voxels by adopting an incremental breadth-first search algorithm. According to the method, for a dynamic complex scene, the number of voxels participating in Euclidean symbol distance field calculation can be remarkably reduced, consumption of a memory and calculation resources is reduced, local increment updating and a sliding window mechanism are supported, high-frequency and low-delay real-time ESDF map construction can be achieved on an embedded or edge platform, and the real-time ESDF map construction efficiency is improved. And the method has good engineering practical value and popularization prospect.

A method and apparatus evaluates a map for autonomous driving. The method acquires pixel points of lane lines of a road in a static map; acquires pixel points of lane lines of the road in a real-time map; forms first fitted curves of the lane lines in the static map by fitting the acquired pixel points of the lane lines in the static map respectively; forms second fitted curves of the lane lines in the real-time map by fitting the acquired pixel points of the lane lines in the real-time map respectively; calculates fitted-curve-similarities between the first fitted curves and the corresponding second fitted curves; and evaluates the consistency of the static map and the real-time map based on the fitted-curve-similarities.

This application provides a real-time trajectory data processing method, apparatus, and system. The method includes: acquiring trajectory data of a moving object and performing denoising processing on the trajectory data to obtain valid trajectory point data; acquiring M candidate road network points of the current trajectory point from the valid trajectory point data; where M is a positive integer; determining a variable sliding window corresponding to the current trajectory point; wherein the length of the variable sliding window is K, the variable sliding window includes N first transition probabilities of the previous trajectory point and a first candidate road network point combination corresponding to each first transition probability, each first candidate road network point combination including K historical candidate road network points, where N and K are positive integers; and performing map matching processing on the M candidate road network points based on the variable sliding window to obtain the road network points of the current trajectory point. This achieves high-precision and low-latency real-time map matching of trajectory data.

The invention relates to the technical field of unmanned ship navigation control, in particular to a multi-source information fusion intelligent navigation control system suitable for an unmanned self-propelled ship, and the system comprises a data collection module which is used for collecting data in a surrounding range with the self-propelled ship as an original point; the data acquisition module is used for acquiring data of the self-propelled ship, the data processing module is used for fusing the data acquired by the data acquisition module and drawing real-time map data with the self-propelled ship as an original point, and the attitude adjusting unit is used for adjusting the navigation attitude of the self-propelled ship according to the real-time map data. And cloud management side end calculation of data is realized through the data processing module and the attitude adjustment unit, and the demand of high-precision attitude control on the computing power of the ship is greatly reduced.

A low-altitude 3D radio map reconstruction method based on scene guidance and sparse measurement is proposed. This method constructs and trains a reconstruction network offline, comprising a sparse data converter module, a radio map data feature extraction module, a multi-scale convolutional pyramid module, and a layer-by-layer radio map reconstruction module. In the online phase, the trained reconstruction network performs real-time map reconstruction. This invention utilizes a deep neural network architecture to fuse environmental scene understanding and sparse measurement data, achieving high-precision, physically consistent 3D reference signal received power (RSRP) field reconstruction, significantly reducing measurement overhead and improving reconstruction quality. By fusing environmental building distribution with sparse RSRP measurements, capturing environmental patterns using feature pyramids, and maintaining vertical dependence through a layered reconstruction strategy, high-precision 3D radio map reconstruction is achieved.

The invention provides an online high-precision map construction method and a model construction method thereof, and the model construction method comprises the steps: sequentially constructing a backbone network, a view conversion network, a hierarchical query embedded network and a model optimization network based on a MapTr model architecture, and obtaining an initial model; training the initial model to obtain a map construction model; and carrying out model integration on the plurality of map construction models to obtain an online high-precision map construction model. According to the method, efficient and accurate high-precision map construction can be realized through a stronger backbone network, an effective view conversion and data enhancement technology and a model integration strategy. The method has excellent performance in the aspect of multi-category semantic information extraction, and is suitable for real-time map construction tasks in an automatic driving system.

The application discloses a map change detection method and device, equipment and a storage medium. The map change detection method comprises the following steps: controlling a movable device to move and record a point cloud based on an acquired prior grid map, and obtaining a real-time grid map; determining an area that is overlapped in the prior grid map and the real-time grid map as a target prior map, and determining an area that is overlapped in the real-time grid map and the prior grid map as a target real-time map; and determining a map change rate of the target real-time map relative to the target prior map based on a grid difference comparison result between the target prior map and the target real-time map. The above scheme can accurately determine whether the current map has changed.

The invention belongs to the technical field of robot navigation, and relates to a precise docking motion control method and system based on a local real-time map, and the method comprises the following steps: 1, obtaining the position and angle of a current point odometer of a mobile charging robot, and then obtaining the position and angle of a target point; 2, judging whether the construction of a local map coordinate system is completed, if the construction of the local map coordinate system is not completed, constructing a local region coordinate system, and if the construction of the local region coordinate system is completed, turning to step 3; 3, converting the current point to a local map; 4, calculating the position and angle deviation of the current point and the target point under the local coordinates; 5, calculating an angular velocity and a linear velocity according to the position and the angular deviation; and 6, releasing the angular velocity and the linear velocity. The method has the effect of constructing the local map according to the target point detected by the starting point and the current odometer data under the condition of not depending on the existing map and not changing the map characteristics.

The embodiment of the invention relates to the technical field of automatic driving, and discloses a strip mine map construction and updating method and device, electronic equipment and a storage medium, and the method comprises the steps: constructing a strip mine map comprising a static map, a road driving area map, a loading area map, a dumping site unloading area map and an obstacle map, performing real-time map updating on the road driving area map, the loading area map, the dumping site unloading area map and the obstacle map; wherein the dumping site unloading area map comprises a retaining wall curve, the retaining wall curve is obtained by processing a comprehensive data matrix through a 3D artificial intelligence model, the comprehensive data matrix is obtained by combining a plurality of data matrixes, and each data matrix comprises coarse curves of a plurality of retaining walls; the coarse curve of each retaining wall is determined based on a frame of sensor data collected during the movement of the driverless truck. According to the mode, a real-time strip mine high-precision map is provided so as to guide, plan and decide operation of various mining area automatic driving vehicles.

An autonomous driving control method receives a HD map and extracts a HD road boundary and a HD lane line based on the HD map. A real-time map displaying a road driving environment of a vehicle is generated using sensor information detected by a sensor mounted on the vehicle. A real-time road boundary and a real-time lane are extracted based on the generated real-time map. The HD road boundary is compared to and analyzed from the real-time road boundary, and the HD lane line is compared and analyzed to the real-time lane. It is determined whether the HD map has changed based on the analyzed result value.

The interaction system includes: an infrastructure image sensor-based 3D cloud restoration module configured to create a 3D cloud point using a multi-view image received from an infrastructure sensor; a real-time 3D map creation and learning update module configured to generate subset data composed of point clouds into a 3D map using 3D point information received from the infrastructure image sensor-based 3D cloud restoration module; an object estimation module in a 3D space configured to recognize and track an object existing in a 3D space based on the 3D map received from the real-time 3D map creation and learning update module; and a dangerous situation recognition and interaction module in space configured to receive information on an object existing in the 3D space from the object estimation module in the 3D space, recognize a dangerous situation, and provide dangerous situation related information.

The invention discloses a vehicle-mounted agricultural product distribution process monitoring system and method, and relates to the technical field of logistics monitoring, and the system comprises an initial scheme module which is used for obtaining distribution task information and real-time map information, and generating an initial distribution scheme; the safety scoring module is used for acquiring real-time driving data of the vehicle to obtain a product safety score of each agricultural product; the in-compartment monitoring module is used for obtaining opening and closing state data of a compartment door and height change data of vehicle suspension after the vehicle arrives at a distribution point to obtain in-compartment change data; the scheme change module is used for adjusting the initial distribution scheme according to the in-compartment change data to generate a subsequent distribution scheme; and the cloud monitoring module is used for generating a real-time delivery report and sending the real-time delivery report to a product receiver. The method has the effect of improving the monitoring efficiency and accuracy in the agricultural product distribution process.

The embodiment of the invention provides a lane-level navigation recommendation method and device, electronic equipment, a vehicle and a medium. The method comprises the steps that passable lanes in a road where the vehicle is located and the extinction distance of the passable lanes are obtained; matching the passable lane and the extinction distance thereof with lanes in a real-time map constructed by the vehicle to obtain a matched real-time map; determining a vehicle surrounding lane set and a target area lane set from the matched real-time map; and determining a target recommended lane from the passable lanes of the target area lane set according to the lane changing direction and the lane changing distance determined by the lane set around the vehicle and the extinction distance of the passable lanes. According to the invention, through the passable lane and the extinction distance thereof, the flow consumption and the dependence on a high-precision map are reduced, and the map source cost is reduced. The passable lane and the extinction distance are matched to the real-time map of the vehicle, so that the dependence on high-precision positioning is reduced, and the accuracy of lane recommendation is improved through the lane changing direction and the lane changing distance.

The embodiment of the invention discloses a goods shelf management method, a control device, a warehouse management system and a readable storage medium, and belongs to the technical field of intelligent storage. The goods shelf management method comprises the steps of obtaining a first warehouse-out scheduling path of each target goods shelf according to real-time map information and a carrying priority corresponding to each target goods shelf by taking the minimum number of carried hindered goods shelves as a target; determining a second warehouse-out scheduling path of each hindering goods shelf by taking the shortest carrying distance of the hindering goods shelf as a target; determining a storage location thermal value corresponding to each storage location in the warehouse, and determining a material thermal value of each goods shelf; according to the warehouse location thermal value and the material thermal value corresponding to each hindering goods shelf, determining a first warehouse returning scheduling path of each hindering goods shelf; and according to the storage location thermal value corresponding to each storage location, determining a second warehouse returning scheduling path of each target goods shelf. Through different paths of a goods shelf management strategy, the balance between the quantity and the path of the goods shelf hindered by minimum carrying is realized.

The present disclosure provides a real-time mapping method and device combined with a navigation map, electronic equipment and a storage medium. In the present disclosure, the real-time mapping method combined with the navigation map comprises: acquiring navigation map data of a vehicle and point cloud data collected by a laser radar on the vehicle; obtaining BEV features of a region around the vehicle according to the navigation map data and the point cloud data through an encoding model; generating a driving region classification map of the BEV by using the BEV features through a first classification model, the driving region classification map containing driving category information of the region around the vehicle; and generating a road structure classification map of the BEV by using the BEV features through a second classification model, the road structure classification map containing road category information of the region around the vehicle. The present disclosure can obtain a real-time map that can be directly used for path planning in combination with a navigation map without using a high-definition map.

1. The name of the design product: road rescue graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for requesting road rescue. 6. The human-computer interaction mode of the graphical user interface: the front view is the road rescue interface, which includes real-time map and real-time positioning above the interface; the input boxes of rescue location and destination, and rescue type are included below the interface; after inputting the rescue location and destination, and selecting the rescue type, the user can click on the call for rescue to realize the request for road rescue. 7. Other circumstances that need to be explained: the gray area above the interface is the real-time map.

Systems and methods for real-time map data coverage optimization are disclosed. A system includes one or more processors configured to determine a real-time map data collection coverage in an interested region, wherein real-time map data are collected by one or more consumer vehicles at locations of the consumer vehicles, determine whether one or more uncovered locations in the interested region are not covered by the locations of the one or more consumer vehicles, in response to determining that the one or more uncovered locations in the interested region are not covered by the locations of the one or more consumer vehicles, generate a route comprising the one or more uncovered locations based on a map of the interested region, and send an instruction to cause operation of a data-collecting vehicle to follow the route for real-time map data collection.

The embodiment of the invention discloses a movement control method and device of an unmanned aerial vehicle, equipment and a storage medium, and belongs to the technical field of unmanned aerial vehicles, the unmanned aerial vehicle is loaded with a laser radar, and the method comprises the steps of calling the laser radar to scan along the movement direction of the unmanned aerial vehicle to obtain first radar data; determining the type of the obstacle based on the first radar data when it is determined that the obstacle exists in the moving direction based on the first radar data; under the condition that the obstacle is determined to be the static obstacle, determining an edge contour of the static obstacle based on the first radar data; and controlling the unmanned aerial vehicle to avoid the static obstacle based on the edge contour. According to the invention, the method determines the edge contour of the static obstacle through the first radar data based on the static obstacle characteristic, controls the unmanned aerial vehicle to avoid the static obstacle based on the edge contour, does not need to construct a real-time map for obstacle avoidance, can reduce the calculation amount needed by the obstacle avoidance control of the unmanned aerial vehicle, and improves the movement efficiency of the unmanned aerial vehicle.

The present application relates to the technical field of engineering safety control, in particular to a three-dimensional real-time map construction method for power transmission and transformation engineering, which sequentially collects substation site clouds, determines initial voxel size according to target volume of drawings, creates voxel grid for thinning, retains any point in voxel space, constructs a three-dimensional map model in sequence according to regions, periodically detects the completeness of model features, if the accuracy is unqualified, determines the reason according to the variance of the difference between target size and drawings, and corrects the thinning mode, thinning parameters and data compression rate; if it is qualified, a three-dimensional real-time map is generated, the target live state, voltage level and safety distance are updated, and a safety operation virtual fence is constructed. The construction method can accurately thin the point cloud data according to the state of the point cloud data and the actual operation demand, thereby efficiently constructing a high-precision three-dimensional map, and providing more accurate and reliable safety protection for nearby live operation.

This invention relates to the field of IoT intelligent control technology and discloses an intelligent system for mosquito control equipment, including a time synchronization and control module, a dual-count fusion module, a multi-dimensional environmental perception module, a prediction and control module, a health assessment module, a regional collaborative optimization module, and a visualization management module. The time synchronization and control module obtains device control commands based on the fusion of BeiDou and GPS dual-channel time signals; the dual-count fusion module combines a weighing sensor and image recognition algorithm to obtain the accurate number of mosquitoes captured; the multi-dimensional environmental perception module collects environmental parameters and performs noise reduction processing; the prediction and control module uses transfer learning and incremental learning to build an activity prediction model; the health assessment module performs local prediction and optimizes the data upload strategy; the regional collaborative optimization module uses weighted Kriging interpolation and particle swarm optimization algorithms; and the visualization management module constructs a real-time map display. This invention enables intelligent management and precise control of mosquito control.

The application provides a navigation method and device based on a depth camera, an unmanned vehicle and a storage medium. The method comprises the following steps: obtaining a target position according to target order information and a preset priority rule; obtaining a current position of a target unmanned vehicle according to the target position, a preset prior map corresponding to a target park and a real-time map corresponding to the target park, wherein the preset prior map is obtained based on a color image and a depth image output by a depth camera, and the real-time map is obtained by processing the preset prior map; performing path planning according to the current position and the target position to obtain an optimal path; and moving the target unmanned vehicle to the target position according to the optimal path. The depth camera is used to obtain a depth image, and a computer directly obtains the depth image, so that additional calculation is not needed, thereby reducing the hardware requirement for the target unmanned vehicle and improving the real-time navigation.

In a first aspect of the invention, it is claimed a computer-implemented method for assisting the movement of a visually impaired user by means of a wearable device 1, comprising the following steps:S1—Acquiring data from the environment of the visually impaired userS2—Fusing the acquired data, creating, repeatedly updating of a Live MapS3—Determining, repeatedly updating and storing, of at least one navigation path together with associated navigation guiding instructions for the visually impaired user to navigate from the current position of the visually impaired user to a point of interest, repeatedly selecting one preferred navigation path from the at least one navigation path, and repeatedly sending to the visually impaired user the preferred navigation path, together with associated navigation guiding instructions.