144results about How to "Realize self-positioning" patented technology

The invention relates to a position fingerprint recognize positioning method, wherein it comprises: fixing positioning area, auxiliary area, and relative names, ranges, and extracting the position fingerprint characters, recognizing positioning, training or retraining; the auxiliary area is outside, inside the positioning area or between it and positioning area; the positioning area is set at the position needed high-accuracy position; the auxiliary area is set at the part without high-accuracy position but affected by the positioning area; the positioning and auxiliary areas can be increased or decreased; the position fingerprint data can be downloaded, uploaded or transmitted; the invention can avoid building large position fingerprint database, and user can accurately position at any place, to realize high-accuracy self positioning at high, middle and low movable terminals, to protect personality, without high cost. And the invention can be based on network or third part positioning, to realize positioning at large range at common accuracy and positioning at special position with high accuracy.

The invention mainly researches a positioning problem when GPS signals are blocked according to vehicle positioning requirements in the Vehicular Ad hoc Network (VANET), and provides a VANET vehicle positioning method based on an in-vehicle inertia device. With the method, a vehicle self positioning capacity when the GPS signals are blocked is improved. With the method provided by the invention, with a vehicle speed sensor, vehicle running speed can be detected; a heading angle is detected with a steering wheel rotation angle sensor; distance increment projection is carried out according to kinematic laws; and the position information of the vehicle at a next time point is obtained, and vehicle self positioning when the GPS signals are blocked is realized. With the method, a combined positioning method is innovated. A dead reckoning (DR) system is composed of gyroscopes in a VSSA system and a SINS system. With the positions and attitude errors of the DR system and the SINS system, and through Sage-husa self-adaptive filtering, the SINS system is compensated, such that SINS system output with relatively high precision can be obtained.

The invention discloses a positioning system for an AGV (Automated Guided Vehicle). The positioning system comprises a global mapping module, a depth learning module, a local mapping module, a matching positioning module and a real-time display module; the working environment is scanned by using laser radar to obtain laser data; meanwhile, a global three-dimensional point cloud map of the workingenvironment is constructed by using a positioning and mapping algorithm; the global three-dimensional point cloud map of the working environment is trained by using a depth learning method so as to obtain a map learning model and a feature matching criterion which are stored into a cloud service side; the local mapping module acquires image data of the working environment in real time by using a Kinect sensor; a local three-dimensional point cloud map of the working environment is constructed according to a pinhole imaging principle. The invention discloses a positioning method for the AGV. The positioning system disclosed by the invention has the advantages that the laser radar is replaced with the Kinect sensor so as to reduce the cost; the global working environment is trained by usingdepth learning; the positioning system realizes real-time positioning of the AGV and has higher robustness.

The invention relates to the fields of an ROS system, a computer vision, image processing and the like and provides an autonomous positioning method for an unmanned aerial vehicle based on vision andimu. The technical scheme is as follows: the utonomous positioning method for the unmanned aerial vehicle based on vision and imu comprises the following steps: collecting an image in front of the unmanned aerial vehicle by means of a monocular camera; reading information of acceleration and angular speed of the unmanned aerial vehicle by means of imu, wherein the monocular camera and imu are synchronized in hardware. The method further comprises the following specific steps of sensing a surrounding environment by means of a camera loaded on the unmanned aerial vehicle to acquire image information and processing the image by way of light stream to track movement. The method is primarily applied to autonomous control occasions of the unmanned aerial vehicle.

A preparation method of a stretchable crystalline semiconductor nanowire based on linear design and guidance of a planar nanowire comprises the steps that 1, standardized cleaning is conducted on glass, silicon dioxide sheet or a silicon wafer substrate; 2, a photoetching or surface pattern etching technology is utilized to etch a step having a certain depth on the surface of the substrate; 3, the crystal nanowire with the diameter of about 130 +/- 20 nm accurately grows along a guiding channel through a planar nanowire guidance growth method to form a nanowire spring array; 4, a metal film is treatment in a PECVD system by utilizing reductive plasmas including hydrogen and the like to form nano metal catalysis particles in the range from dozens of nanometers to one micrometer; 5, an amorphous semiconductor layer having appropriate thickness deposits in a covering mode to serve as a precursor medium; 6, annealing growth is performed in a vacuum or nonoxidative atmosphere, and an amorphous layer is absorbed and a crystalline nanowire structure deposits in the way at the temperature of 250 DEG C or above.

The invention relates to a grid-clustering-based RSSI (Receive Signal Strength Indicator) indoor positioning algorithm which comprises the following steps: S1, placing an RFID (Radio Frequency Identification) fixed reader, randomly placing an active tag as a to-be-detected tag, and determining an RFID positioning system model; S2, repeatedly measuring the RSSI value from each reader to the to-be-detected tag at different moments, recording the measured value each time, and calculating the distance from the to-be-detected tag to each reader according to the acquired RSSI value; S3, acquiring aplurality of 'estimation tags' by using a trilateration algorithm, solving the mean of the coordinates of the 'estimation tags' as a 'target tag'; S4, defining a search region by taking the 'target tag' as a center, and dividing the region into grids of the same size; S5, screening the grid containing the most 'estimation tags' by utilizing a grid clustering algorithm, and selecting the 'estimation tags' in the grid as reference tags; S6, solving the centroid of the reference tags as the estimated value of the to-be-determined tag coordinate according to a weighted centroid algorithm.

The invention relates to a Beidou navigation method based on fusion of robust adaptation and extended Kalman filtering. The Beidou navigation method based on fusion of robust adaptation and extended Kalman filtering includes the steps: a) acquiring positioning data; b) establishing a state observation equation with a rough error; c) establishing state estimation; d) solving an observation value variance matrix; e) acquiring adaptive filtering solution; f) estimating an error variance matrix; g) performing robust adaption filtering. The Beidou navigation method based on fusion of robust adaptation and extended Kalman filtering has the advantages that the Beidou navigation method based on fusion of robust adaptation and extended Kalman filtering is obviously superior to a least square methodand a Kalman filtering method, and has a certain degree of improvement compared with the extended Kalman filtering method, and the error precision is about 5cm, thus satisfying the accuracy requirement for automatic driving of agricultural machinery, being able to be combined with a high-performance controller to effectively control the steering and speed of agricultural machinery, and being ableto achieve the aim of autonomous positioning, automatic track tracking and automatic driving of the agricultural machinery.

The invention relates to the technical field of wireless sensors, and discloses a wireless sensor network node self-positioning method based on a mobile anchor node, which is used for solving a problem of high complexity when a mobile anchor node positioning method is adopted. The method comprises the following steps of: building a two-dimensional rectangular plane coordinate system by aiming at a monitoring area so as to locate a sensor network monitoring area in a first quadrant completely and position an initial position of the anchor node in the origin of coordinates. The anchor node does not move when positioning broadcasting location information at interval or positioning the broadcasting location information, all the unknown nodes can receive the location information through rotating a directional antenna and store the received location information and signal strength, and the location information with the largest signal strength is selected as the available self-positioning data after the unknown nodes do not receive the location information. All the unknown nodes receive different location information for at least two times along with the movement of the anchor node, and a self position is computed through utilizing the selected available self-positioning data.

The invention provides a three-dimensional laser scanner fixing mechanism, a subway tunnel acquisition system and method. The subway tunnel acquisition system includes a three-dimensional laser scanner fixing mechanism, a rail car module, a distance sensor, an RFID reader and a host computer; the three-dimensional laser scanner The point cloud data of the tunnel ring is collected continuously, the distance sensor collects the mileage data in real time and transmits it to the host computer, and the RFID reader returns the read and written RFID smart label signal to the host computer in real time, and the host computer The computer completes multi-source data fusion and storage. The invention solves the problem that the automatic motor of the three-dimensional laser scanner cannot be locked in the section scanning mode, and avoids the damage to the scanner caused by misoperation. Through the integrated design of the two modules of the constant speed rail car and the 3D laser scanner, the quality of the collected data is improved, the automatic collection of tunnel deformation data and disease information is realized, the labor cost is reduced, and the detection efficiency is improved.

The present invention discloses an ultra-wideband node network-based device-free localization method, belonging to the field of wireless localization technologies in a wireless network. According to the method, an ultra-wideband signal is sent by using a node so as to realize device-free localization (DFL), a channel pulse response in a line of sight (LOS) is detected, and localization is performed by using change of an LOS path signal power. In addition, the ultra-wideband node has a precise distance measurement capability, and can achieve precise node self-localization. Node self-localization is achieved by using distance measurement provided by the ultra-wideband node according to a cooperation localization method, shadow fading caused by shielding by a target is obvious, and an imaging effect is further improved, so that the method is more applicable to an environment with low LOS power, can improve localization precision in a more complex environment, and greatly reduces manpower and time cost for node deployment.

The invention provides a vehicle self-positioning method, device and system. The method comprises the steps of: obtaining a road image around a vehicle, and the initial position of the vehicle and theposture information of the vehicle corresponding to a road image collection moment; obtaining a reference object of the vehicle in a forward preset distance range in a high-precision map; matching the projection of a target object recognized from the road image with the projection of the reference object on the road image; and resolving the coordinates of a vehicle camera according to a matchingresult, wherein the coordinates of the vehicle camera are used for representing the position of the vehicle, and the vehicle camera is installed at a preset position of the vehicle. According to the method, the perception of the environment can be completed by only depending on a monocular camera, and the perceived target object is directly matched with the mapping point of the reference object inthe high-precision map from 3D to 2D, so that the self-positioning of the vehicle is quickly realized, and the hardware cost is greatly reduced on the premise of ensuring the positioning precision.

The invention discloses a pedestrian self-positioning method based on audio/video multi-source information fusion of a smartphone. A pedestrian is subjected to acoustic positioning and visual positioning; finally, for positioning results, a pedestrian state equation is processed with a UKF (unscented Kalman filter) algorithm, nonlinear problems in the equation are observed, fusion of acoustic range, PDR positioning and visual position is performed independent of infrastructure of application places, and pedestrian self-positioning adopting indoor and outdoor seamless connection is realized. Positioning errors can be reduced to subnanometer scale from nanometer scale through correction of PDR results by pseudo-ultrasonic ranging, meanwhile, a positioning system cannot be affected by inertial navigation drifting in combination with data information of visual gyro and a visual odometer, infrastructure of application places is not depended, and the universality and robustness are better. The method is applicable to pedestrian self-positioning in indoor and outdoor environments.

The invention discloses a wifi and geomagnetism fused indoor positioning system and method based on an HMM (Hidden Markov Model). The method comprises the following steps: matching a wifi signal acquired by a mobile terminal in real time with a pre-established wifi fingerprint library to obtain a local position area; initializing the position in the area to obtain an initial probability distribution matrix; obtaining a state transition probability matrix by using a position relationship of label points in the local position area; and fusing a geomagnetic signal with a pre-established geomagnetic fingerprint library to obtain an observation probability matrix, and estimating the position of a user according to a forward algorithm. When the user is positioned in the local position area determined by the wifi signal, the current real-time geomagnetic signal is used to update the observation probability matrix, and the position of the user is estimated by the observation probability matrixand the state transition matrix; otherwise, the wifi signal is introduced to re-establish the local position area, and the initial probability distribution matrix, the state transition probability matrix and the observation probability matrix are updated according to the preceding method. According to the wifi and geomagnetism fused indoor positioning method based on the provided by the invention, various information is effectively fused, and the positioning accuracy of the system is improved.

The invention relates to an indoor autonomous positioning method of a mobile robot which combines the point and line characteristics of a scene. The method has strong scene adaptability, which uses adepth camera mounted on a mobile robot to collect scene video data, and extracts the point and line features of each frame of the scene to complete the subsequent positioning calculation. Generally, point features perform well in clear texture, rich feature points and unobstructed scenes. However, in the scene with fewer texture feature points, there is a problem of scarcity of feature points, andthe robustness of the simple feature point location method is poor. The invention extracts more stable object line features in the scene with missing texture, thereby ensuring to provide more abundant feature information to realize the calculation of the visual odometer, thereby obtaining the position information of the mobile robot and achieving the purpose of autonomous positioning.

The invention discloses a typhoon center positioning method based on deep reinforcement learning. According to the method, the perception ability of deep learning and the decision ability of reinforcement learning are combined, a typhoon center positioning problem is converted into a series of decision behaviors of searching a typhoon center on a satellite cloud picture by utilizing a search box,a Markov decision-making process is used for modeling in the search process, an intelligent agent is trained through a deep reinforcement learning algorithm to learn and move and reduce a search box through simple operation, the center of the search box is made to be close to a real typhoon center constantly, and then typhoon center autonomous positioning is achieved. According to the method, typhoon detection and center positioning of different levels and different forms are achieved, and the effectiveness of the method is verified through experiments.

The invention discloses a two-dimensional-code recognition method and a robot visual-navigation self-positioning method based thereon. A manner of apex angle positioning squares of an encoding patternof a two-dimensional code includes respectively arranging a positioning square at each of three of four apex angles of the encoding pattern of the two-dimensional code, and forming a middle nine-square encoding region by 3*3 numerical squares. According to the recognition method, horizontal and vertical division of nine regions are carried out on nine-square encoding regions to obtain corresponding binary numbers by decoding, view angle directions and a binary character string of each numerical square are determined according to different position combinations of positioning squares, data information of two-dimensional codes is obtained, two-dimensional-code information can be accurately extracted, and recognition is carried out according to the different view angle directions. Accordingto the robot visual-navigation self-positioning method, different intersections are marked through a nine-square encoding scheme, robot autonomous-positioning is realized according to encoding resultsof visual recognition, thus autonomous walking according to a set plan path is realized, costs are low, and the self-positioning method is also simple and reliable.

The invention discloses a multi-module position module based on the satellite position, which comprises a GPS OEM board with up-and -down structure and a DR circuit plate, wherein the two parts are connected with each other by the interface; the multi-module position module also possesses a position beacon interface, a matching electric map interface, an angle speed measuring unit, a car mileage and reverse signal matching receiving circuit, a MCU CPU, a computer communication interface and a power managing module.

The invention discloses a vehicle self-positioning method and system based on an auxiliary positioning line, and belongs to the technical field of automatic driving. The method comprises the steps ofadding the auxiliary positioning line on a road surface with complete lane line information, the auxiliary positioning line being a physical line length having a mapping relationship with a code element sequence; acquiring image information of lane lines and auxiliary positioning lines on the road surface; and identifying the images of the lane line and the auxiliary positioning line, and positioning the position of the vehicle in the road according to the identification result. The vision processing method is used for processing the image containing the auxiliary positioning line, the accuracy of vehicle self-positioning is guaranteed, meanwhile, only the positioning auxiliary line needs to be additionally arranged on the road surface, and the cost is lower.

The invention discloses a single-satellite autonomous positioning method adopting an area array optical payload. The method comprises the following steps: S1, obtaining a remote sensing image after earth observation, matching the remote sensing image with a ground mark point information bank, extracting all ground mark points included in the remote sensing image, and selecting three ground mark points for positioning from all the ground mark points; S2, performing spatial geometric position modeling on the three ground mark points for positioning, and obtaining a spacecraft positioning model in combination with a geometric relationship among a ground mark point coordinate system, a camera coordinate system, an image plane coordinate system and a geocentric inertial coordinate system; and S3, solving the spacecraft positioning model by adopting a preset processing algorithm to obtain single-satellite autonomous positioning output so as to complete autonomous positioning of a single satellite. According to the method disclosed by the invention, autonomous positioning can be completed by only using spacecraft earth observation payloads, so that a spacecraft can easily fit out spacecraft orbit parameters to enable a spacecraft measuring orbit to break away from external conditions, and the interference immunity and reliability are greatly enhanced.

The invention provides a post-disaster rescue hexapod robot autonomous detection system and method, and relates to the field of robot technology application. The system comprises a control module, a sensing module, an execution module and a monitoring module, wherein a hexapod robot adopts an improved artificial potential field method for autonomous detection, when a post-disaster wounded person is not detected, a set value of a GPS and inertia measurement unit serves as a target point for movement of the hexapod robot; when the post-disaster wounded person is detected, the hexapod robot changes priority of sensors, and the position of the post-disaster wounded person serves as a target point where the hexapod robot moves. The system is advantaged in that the hexapod robot fuses ultrasonicwave and infrared photoelectric switch data through a neural network algorithm so as to realize obstacle avoidance and obstacle crossing of the hexapod robot, a Kalman filtering algorithm is adoptedto fuse GPS and inertial measurement unit data to complete autonomous positioning and navigation of the hexapod robot, reasonable arrangement of an infrared pyroelectric sensor is combined to completeperception and positioning of the post-disaster wounded person, and the autonomous detection function of the hexapod robot is achieved.

The invention relates to a method of preparing a three-dimensional super-stretchable crystalline nanowire, which comprises the following steps of: (1) depositing an insulating dielectric layer on a substrate as a sacrificial layer by using PECVD or PVD, (2) defining a periodic step edge pattern by using photoetching and electron beam direct writing, and etching the dielectric layer by using a drymethod or wet method alternate etching process to form vertical step side walls, 3) treating the surface of the step with corrosive liquid to form a wavy step, 4) defining a pattern vertical to the step by photoetching electron beam direct writing or a mask plate technology again, and preparing a secondary guide channel vertical to the step by an etching technology, 5) locally depositing a strip-shaped catalytic metal layer through a photoetching, evaporation or sputtering process, (6) converting the catalytic metal layer into separated metal nanoparticles, and (7) reducing the temperature tobe lower than the melting point of the catalytic metal particles, depositing and covering an amorphous semiconductor precursor film layer on the surface of the whole structure, depositing crystallinenanowires, and enabling the nanowires to grow along the guide channel of a wavy step.

The invention discloses a semi-ring coupled precision rolling bearing. The semi-ring coupled precision rolling bearing comprises a bearing inner ring, a bearing outer ring, a rolling element positioned between the bearing inner ring and the bearing outer ring as well as a retainer, wherein the bearing inner ring is formed by connecting an inner ring semi-ring a and an inner ring semi-ring b; the bearing outer ring is formed by connecting an outer ring semi-ring a and an outer ring semi-ring b. The semi-ring coupled precision rolling bearing disclosed by the invention is convenient and simple to assemble and disassemble; the semi-ring coupling surface of the bearing inner ring can be laminated with the semi-ring coupling surface of the bearing outer ring and self positioning of the couplingsurface is realized, so that the bearing inner ring has higher roller path docking precision and the semi-ring coupling surface of the inner ring is enabled to have higher coupling rigidity of the coupling surface.