575 results about "Local map" patented technology

When information regarding position of a facility, such as a parking lot, is requested from a terminal (22), an information center (10) supplies position information to the terminal (22) as a relative position using a landmark, such as a neighboring road. The terminal (22) computes a shift from a position of a landmark in a local map database (24) and a position of a received landmark in a map matching processor (34), and corrects the facility position. If the landmark has not been stored in the map database (24) at the terminal (22), relative data based on another road is resent.

Information communication technology operable to provide users with a means for sharing information and comments is disclosed. The information communication technology provides a means for participants to place chat comments on an interactive graphic such as a dynamically rendered map that participants can track, edit and collaboratively work with in order to decide on a suitable meeting location.

The invention relates to a system and method for generating a lane-level navigation map of an unmanned vehicle based on multi-source data. The lane-level navigation map comprises an offline global map part and an online local map part. According to an offline module, within a target region where the unmanned vehicle runs, original road data is acquired through satellite photos (or aerial photos), a vehicle sensor (laser radar and a camera) and a high-precision integrated positioning system (a global positioning system and an inertial navigation system), then the original road data is subjected to offline processing, multiple kinds of road information are extracted, and finally the road information extracting results are fused to generate the offline global map. The offline global map is stored through a layered structure. According to an online module, when the unmanned vehicle automatically drives in the target region, the road data in the offline global map is extracted according to real-time positioning information, and the online local map with the vehicle as the center within the fixed distance range is drawn. The system and method can be applied to fusion sensing, high-precision positioning and intelligent decisions of the unmanned vehicle.

Embodiments of the invention relate to a determination method and apparatus for the position and orientation of a mobile robot. The method comprises the following steps: in virtue of simultaneous localization and mapping (SLAM) technology, establishing a global map of an environment where the mobile robot plays a navigation role by using a laser scanner; when the mobile robot is energized, establishing a local map of an environment in the energization moment of the mobile robot by using a laser scanner in virtue of SLAM technology; and subjecting the local map to image matching in the global map so as to obtain the initial position and orientation of the mobile robot in the global map. According to the embodiments of the invention, the absolute position and orientation of the mobile robot in the global map in the moment the mobile robot is energized and started can be obtained, thereby realizing initialization of the position and orientation of the mobile robot; moreover, determined position and orientation of the mobile robot can be further corrected.

An apparatus and method facilitate combined query based searching with serendipitous browsing in a multimedia collection. A user selects objects to label from a local map, which may include representations of objects retrieved from the collection as being responsive to a text or image base query. The text and image portions of the object can be independently labeled. Unlabeled objects are scored and ranked based on the applied labels of labeled objects, which may take into account cross-media pseudo-relevance and user selectable (or default) parameters, such as a forgetting factor, which tends to place greater weight on more recently labeled objects, and a modality parameter, which laces greater weight on the modality (text, image, or hybrid) currently selected by the user. The local map is modified, based on the ranking, optionally after reranking of objects to improve the diversity of the displayed objects.

The invention discloses a lane line detection and GIS map information development-based vision navigation method. The method comprises the following steps: acquiring GIS map information, preprocessing, carrying out real-time image acquisition and lane line detection to generate a GIS local map in real-time, carrying out coupling verification on a track line detection result and the GIS local map through an ICP algorithm, and generating a high-credibility track line result according to the coupling result. The method can realize the credibility evaluation of the lane line detection through a geographic information system, corrects when false detection or missing inspection appears, expands the application range of the lane detection algorithm, and also can improve the map positioning precision through visual perception information, so the performances of a vision navigation system in a whole intelligent driving and aided driving system are improved, thereby the system can adapt to more complex environments.

The invention relates to a multi-information-fusion-based high precision localization method for an unmanned vehicle, and the multi-information-fusion-based high precision localization method can be applied to environment perception and intelligent decision-making of the unmanned vehicle. Through cooperation of an offline map and online sensing information, high-precision real-time positioning can be realized. The offline map records road traffic information of a driving area of the unmanned vehicle. The online sensing information includes lane lines and road boundaries. When the unmanned vehicle runs in a map area, according to location information given by an inertial combined navigation system, an approximate location of the vehicle is determined, a local map near the approximate location is obtained, the lane lines in front of the vehicle and the road boundaries on both sides of the vehicle can be detected by a vehicle sensor, the relative position of the vehicle and the lane lines and the road boundaries can be determined, by contrast of the location of the vehicle in the map, deviation is calculated, a location error is corrected, and high-precision localization can be achieved.

The invention discloses a mobile robot indoor environment exploration system and control method based on a ROS (Robot Operating System). The system is based on the ROS, and can realize independent exploration and positioning on indoor environment by a robot. The system mainly uses an iRobot differential drive chassis and UTM 30LX laser radar. An upper computer can obtain position positioning information of the robot and an indoor environment exploration path track in real time, and through data matching of the laser radar, a global map formed by connecting local maps is obtained. The invention provides a more intelligent unknown environment exploration system, provides great convenience and safety guarantee for disaster environment rescue, realizes information interaction of indoor environment perception, and has very good convenience and practicality.

The invention discloses a vSLAM implementation method and system based on point and line feature fusion. The method includes Step S110, obtaining an image frame sequence of a target scene; Step S120,preprocessing each frame of image; Step S130, according to successfully matched point features and lie features, initializing an environmental map; Step S140, tracking based on the environmental map,and estimating the pose of a current frame of image; Step S150, judging whether the current frame of image meets a key frame condition, if yes, executing Step S160, otherwise repeatedly executing StepS110 to Step S150; Step S160, executing a step of a local map thread; Step S170, executing a step of a closed-loop detection thread; and Step S180, executing a step of a global optimization thread toobtain an optimized environmental map and complete simultaneous localization and mapping. The extraction and matching processes of line features are improved, so as to improve the accuracy of data association in the front end, and thus the defects of vSLAM which exist in a complicated low-texture scene can be effectively overcome.

The invention discloses a vehicle positioning method and system. The positioning system comprises a GPS module, an IMU module, a camera module, a laser module and a controller module. When a vehicle drives in a shielded traffic environment, the positioning precision of the vehicle by the GPS module is lower than a preset positioning precision, the controller module turns on the camera module and the laser module, and preliminary positioning of the vehicle is performed by employing a road environment image acquired by the camera module; a local map corresponding to a preliminary positioning result is determined from a pre-stored map; three-dimensional map reconstruction is performed by employing 3D point cloud data, scanned by the laser module, of a vehicle surrounding environment; and thereconstructed three-dimensional map and the local map are matched to obtain practical position information and course angle information of the vehicle. According to the method and system, problems ofinaccurate positioning and accumulative errors of the GPS module in the shielded traffic environment are effectively avoided, and the accuracy of vehicle positioning is improved.

The invention discloses a method and a system of mobile terminal navigation applied in small-bandwidth wireless network. The system comprises a mobile terminal and a GNSS receiver connected with the mobile terminal. The mobile terminal is also connected with a local map database for local searching and managing navigation information. The mobile terminal is connected with a navigation server through wireless network. The navigation server comprises the map database for storing the map information and a real-time dynamic information database. The method comprises that after receiving a navigation request sent from the mobile terminal, the navigation server will obtain the navigation information according to the server map database and the real-time dynamic information database and send the navigation information back to the mobile terminal; the mobile terminal manages the local map and marks the navigation information on the local map and outputs the display module. The invention greatly reduces the data transmission so that large capacity of map won't cause a navigation default in small-bandwidth environment.

The invention discloses an intelligent vehicle positioning method based on multi-sensor information fusion. The drifting phenomenon produced by the fact that GPS positioning is merely depended can be effectively avoided, and accordingly the vehicle positioning precision is improved. The position of a vehicle in a local map by processing radar data and encoder data and adopting a synchronous positioning and map establishing method (SLAM), the position of the vehicle in a longitude and latitude system is obtained through GPS positioning, the positions are unified to a geodetic coordinate system through coordinate transformation, and fusion processing is conducted on the position information by using a Kalman filter to obtain accurate estimation of the vehicle position. Accurate global vehicle location is achieved based on a vehicle-mounted encoder, laser radar and GPS.

The invention discloses a simultaneous localization and mapping (SLAM) method for an unmanned aerial vehicle based on mixed vision odometers and a multi-scale map, and belongs to the technical field of autonomous navigation of unmanned aerial vehicles. According to the SLAM method, an overlooking monocular camera, a foresight binocular camera and an airborne computer are carried on an unmanned aerial vehicle platform; the monocular camera is used for the visual odometer based on a direct method, and binocular camera is used for the visual odometer based on feature point method; the mixed visual odometers conduct information fusion on output of the two visual odometers to construct the local map for positioning, and the real-time posture of the unmanned aerial vehicle is obtained; then theposture is fed back to a flight control system to control the position of the unmanned aerial vehicle; and the airborne computer transmits the real-time posture and collected images to a ground station, the ground station plans the flight path in real time according to the constructed global map and sends waypoint information to the unmanned aerial vehicle, and thus autonomous flight of the unmanned aerial vehicle is achieved. Real-time posture estimation and environmental perception of the unmanned aerial vehicle under the non-GPS environment are achieved, and the intelligent level of the unmanned aerial vehicle is greatly increased.

The embodiment of the invention discloses a map building method and a robot control system. Map building can be achieved more easily. The map building method comprises the steps that a feature point of a current frame is extracted; a feature point of a reference frame is obtained, and a current pose is obtained according to the feature point of the current frame and the feature point of the reference frame; a cumulative error existing is estimated by means of the pose obtained through frame-to-frame registration, and a feature point of a key frame in a local map is projected to the current frame; and when the current frame conforms to the condition of the newly-added key frame, the key frame is inserted into the local map.

The invention discloses a geographical environmental characteristic map construction and navigation method based on data mining, and belongs to the field of automatic control. The method comprises the following flow: firstly performing processing and matching on a current 3D laser-point cloud of the surrounding environment of a platform and a panoramic picture, to acquire characteristic vectors of each object in the platform surrounding environment; secondly inputting the characteristic vectors of each object into a neural network which classifies the characteristic vectors and outputs a characteristic environmental model; thirdly according to the characteristic environmental model, establishing a current local map or updating an original local map; and finally based on a current position of the platform and a predicted next-moment position, selecting a routine for driving according to the local map. If the platform does not reach a final goal, the flow is repeated; and if the platform reaches the final goal, the flow is finished and the final local map is a global map. The method is applicable to geographical environment map construction and navigation of a ground unmanned mobile platform.

The invention discloses an ORB-SLAM based high-precision vehicle positioning method, which mainly solves a problem of low accuracy of the positioning result of the current ORB-SLAM classical positioning algorithm. The implementation of the method comprises the steps of selecting a calibration board to calibrate a binocular camera, and carrying out stereo correction on a captured image; detecting ORB feature points in the corrected image, and completing the feature point extraction; matching the extracted feature points by using a binocular sparse feature matching method, then acquiring the current camera pose information by using an adjacent frame feature tracking method, and constructing a local map; carrying out closed-loop detection and global optimization on the constructed local map so as to complete the establishment of a visual map, and preserving the visual map; and selecting a vehicle positioning scheme according to the number of matched feature points in the image, and determining the final position of the target vehicle through reading the visual map. The method disclosed by the invention can improve the vehicle positioning accuracy and robustness, and can be used for artificial intelligence management and safety disposal of unmanned automobiles.

The invention discloses a raster map building method based on local map splicing.The method comprises the following steps that 1, a robot scans and records environment information; 2, scanning data points are filtered to remove useless points; 3, local raster maps are calculated based on the filtered data through a ray tracking method; 4, sift feature points and corresponding feature descriptors of the local raster maps under two adjacent poses are calculated; 5, according to relevancy of the feature descriptors, the feature points are ranked, and feature points with small feather feature descriptors are filtered away; 6, the two local maps are subjected to iterative closest point algorithm ICP, and a transformation matrix of the two local maps is calculated; 7, the steps 1-6 are repeated, a transformation matrix of the whole path is recorded and completed, and finally data is merged to obtain a global raster map.The map is built through one-time laser data, so that the estimation error of the map is mainly the observation error of a laser sensor, and no estimation error exits.

This invention relates to mobile robot technique based on earth seam intelligent car visual device and its whole layout position method, which comprises the following steps: a, establishing environment layout earth seam map into system; b, sending the caught image signals by data line or collection program into top layer process unit; c, top layer process unit processes images to extract image seam information to form one local earth seam map; d, using intelligent mile information to reduce local map index range; e, searching the current local earth map and whole earth seam map.

The invention discloses a method for protecting position privacy by mobile terminals. According to the method, the mobile terminals are used for forecasting moving tracks of terminal owners in a period and refining and amending the moving tracks according to a local map. For the terminal owners which are close to each other, each mobile terminal takes a position where the owner of the mobile terminal exists as a start point, and positions forecast by the other owners are taken as terminal points. A map navigation service is utilized to generate a fake route, the fake route is mixed with a true route, and the fake route and the true route are combined to generate complete two branch route pictures. Each terminal owner performs fake name replacement at end points of the complete two branch pictures, the owners can be mutually indistinguishable, and therefore privacy protection is achieved. According to the method for protecting the position privacy by the terminal mobile, the position privacy of the mobile users is protected, meanwhile, reduction of precision in issuing position information is not needed, and therefore the functionality for accessing the LBS service by mobile users based on the position information is ensured.

The invention relates to an inspection robot navigation system and method based on RTK Beidou and a laser radar. The inspection robot navigation system based on RTK Beidou and laser radar includes a robot movement station and a background management server, wherein the robot movement station includes a robot body, a control module, a positioning navigation module, a wireless communication module and a power supply management module; the control module, the positioning navigation module, the wireless communication module and the power supply management module are arranged on the robot body; thepositioning navigation module includes a laser radar and an RTK/SINS unit; a navigation map employs the design scheme combined with a global map and a local map; the global map construction draws ina mode that the robot records the track, and the navigation mode uses a preview PID algorithm; and the local map construction employs the laser radar to record the obstacle discrete data points and restore the obstacle edge information through the clustering step, the curve fitting step and other steps, and uses the artificial potential field path planning obstacle avoidance mode. Compared with the prior art, the inspection robot navigation system and method based on RTK Beidou and a laser radar have the advantages of being high in navigation positioning precision, having no demand for pavement reconstruction, being high in environment adaptability, and being high in work stability.

The invention provides a signal lamp state terminal display method and a system based on a cooperative vehicle infrastructure technology. The system comprises a traffic signal machine, a roadside module, a vehicle infrastructure communication module and a terminal device, wherein the traffic signal machine is used for generating signal lamp phase timing information and transmitting the information to the roadside module; the roadside module is used for publishing intersection position information, local MAP information and a real-time SPAT information; the vehicle infrastructure communication module is used for information data interaction between the terminal device and the roadside module; and the terminal device is used for acquiring, processing and displaying the vehicle motion state data and terminal information. The cooperative vehicle-infrastructure technology is used for realizing real-time displaying of the signal lamp state on the terminal device, a driver can conveniently judge the vehicle passing time and the queue time, the road traffic safety is enhanced, the road traffic pressure is reduced, influences from the environment, the vehicle and the driver do not exist, and the system use efficiency is high; and red lamp early warning or automatic control can also be realized, the intersection driving safety is ensured, and a behavior of running the red lamp to break the law can be avoided.

The invention discloses a robot synchronous positioning and map construction method based on line segment features and line segment vanishing points, and the robot synchronous positioning and map construction method is applied to the positioning and map construction of a robot in an unknown environment. The robot synchronous positioning and map construction method comprises the steps of: extracting line segment features, intersection points and vanishing points from images, establishing line segment matching between the images according to the intersection points, estimating camera poses according to line segment matching results, and selecting a new keyframe; and inserting the keyframe into a map, calculating three-dimensional coordinates of the newly-added line segment features, performing cluster adjustment on local map, and removing outlier observation; and performing closed-loop detection and global map optimization based on the intersection points. The invention further discloses a synchronous positioning and map construction system. The robot synchronous positioning and map construction method and the robot synchronous positioning and map construction system can be appliedto the positioning and map construction of the robot in the unknown environment, and is particularly suitable for structured or semi-structured scenes, such as indoor environments, outdoor environments with buildings, and the like.

The invention provides a robot indoor environment exploration,obstacle avoidance and target tracking method based on a ROS. Based on a grid map established through laser radar information,combined with local map deduction and global boundary searching,an independent exploration strategy is designed so that a moving robot can be prevented from getting into a local exploration infinite loop,and whole-indoor-environment exploration can be completely guaranteed. According to the method,real-time tracking nodes and shielding tracking nodes are designed with an improved Kalman filtering method and aMeanShift method in the ROS,the real-time problem and the complete-shielding problem of target tracking of the moving robot are solved,the computing speed of the system is increased,target search time is shortened,and the real-time requirement of tracking is met; when a target is completely shielded,the shielding tracking nodes forecast and track the target according to previous state information,and after shielding is ended,a target is newly locked,tracking modes are automatically switched,and the target is tracked through the real-time tracking mode.