73results about How to "Reduce positioning impact" patented technology

The present invention belongs to node self-localization field in large-scale wireless sensor network, and discloses a node indoor localization method based on wireless signal intensity, which main includes: getting relationship curve of signal intensity and distance, and putting forward concept of effective wireless signal intensity (Effective RSS, ERSS); obtaining coordinates of target node by selecting localization arithmetic (ERSS filter + maximum likelihood estimation, triangle localization, approximate location estimation) according with anchor point amount through distance between anchor point and target by training RSS curve; providing alerting service by using physics coordinate, providing navigation service according with route arithmetic and address chain by using sign coordinate (for example in hall). Precisely localization of indoor target can be realized in condition of low-cost, simple initial configuration, and a plurality of services based on location can also be provided.

The invention discloses a threshold value-based optimized weighted centroid positioning method in a WSN. The method is characterized by comprising two parts, namely beacon node combination optimization and weighted centroid positioning computation; in the first part, unknown nodes select n nearest beacon nodes, each three beacon nodes form a combination, whether a combination meets conditions or not is judged, and beacon nodes meeting conditions are used for weighted centroid computation; in the second part, an overlapping zone is divided into four parts, the ratio of the area of each part to the total area serves as a weight number, and the centroid of each part is subjected to weighted computation so as to obtain coordinates of the unknown nodes. The optimized algorithm reduces positioning error and improves the node positioning accuracy.

The invention discloses a method for controlling smart televisions via three-dimensional gestures on basis of binocular structured light. The method comprises the following steps of: synchronously acquiring images through a binocular camera; reconstructing a three-dimensional image according to an obtained left-right view; carrying out preprocessing; recognizing a gesture action after three-dimensional gestures are segmented; and converting the recognized gesture action into an operation instruction for a smart television, and executing the operation instruction. According to the method, a binocular vision and structured light combined manner is adopted, so that the environmental anti-interference ability can be effectively improved, the influences, on fingertip positioning, of light conditions can be reduced, and the timeliness and effectiveness of smart televisions can be satisfied.

The invention belongs to the technical field of robots, and particularly relates to a robot map updating method and device, a computer readable storage medium and a robot. The method comprises the steps : in the mapping process of a robot, generating all sub-graphs in sequence, wherein each sub-graph is a local map comprising a plurality of frames of data; constructing a global map according to each sub-graph; executing loop-back optimization, and selecting a target sub-graph from all the sub-graphs, wherein the target sub-graph is a sub-graph, changed before and after loop-back optimization,of the pose of the robot in the frame data; and updating the global map according to the target sub-map to obtain an updated global map. According to the method, only partial updating of part of the sub-graphs is involved, the calculation amount is greatly reduced, the map updating efficiency is improved, map updating can be completed in a short time, the influence of map updating on robot positioning is reduced, and the situation that the pose of the robot is wrong or even lost is avoided.

The invention discloses a sound source positioning method and system, electronic equipment and a storage medium. The sound source positioning method comprises the steps of dividing a voice signal received by a reference microphone into at least one sub-band, wherein the reference microphone is one microphone in a microphone array; if voice exists in the voice signal through VAD detection, for eachsub-band, calculating the voice existence probability according to the likelihood ratio of voice relative noise obtained in the VAD detection process; and calculating the maximum controllable response power of the microphone array by using an SRP-PHAT algorithm based on sub-band voice existence probability weighting, and determining the direction of the sound source according to the angle corresponding to the maximum controllable response power. According to the invention, the voice existence probability of each frequency band is calculated by utilizing the intermediate result of the VAD detection voice and is weighted into the original SRP-PHAT algorithm, so that the sound source positioning performance under the low noise ratio is improved under the condition of not increasing the additional calculation amount.

The invention discloses a wireless-sonic-transducer-network-based multi-node inflation fusion sound source positioning method. With the method, a technical problem of low precision of the existing sound source positioning method can be solved. According to the technical scheme, a kalman filter is used for carrying out fusion on a near-field positioning result and a far-field DOA estimation value of a sound source. During an iteration process, a prediction result is corrected continuously according to an error covariance matrix until a final sound source positioning result is obtained; and the positioning precision can be improved by the iteration optimization process. When iteration fusion of a far-field node DOA estimation value is carried out each time, a positioning node is elected dynamically from a node set, so that the influence on positioning by a single node estimation error can be reduced and the noise immunity is improved. Because of the kalman filter method, the near-field positioning result of the sound source is added and is fused with the far-field node DOA estimation value of the sound source; and the sound source positioning precision is improved based on the iteration optimization process, wherein the positioning precision is improved by 1% to 3%.

The invention relates to a wireless Internet of vehicles and things positioning system. The positioning system includes a plurality of vehicles and a plurality of street lamps arranged at roadsides; each street lamp is provided with a microprocessor, a first LTE communication module, a memory for storing street lamp geographic positions, a signal modulator, a first spreading code generator, a spread spectrum modulator, a first photoelectric signal converter and an LED light source; the LED light source is uniformly provided with a plurality of individually-numbered square LED light emitting lattices; black light LEDs, blue light LEDs, green light LEDs and red light LEDs are arranged in the light emitting lattices; each vehicle is provided with a central processor, a Bluetooth module, a second LTE communication module, a GPS positioning module, a positioning signal identification generator, an optical signal intensity detector, an optical signal receiver, a noise filtering device, a signal comparator, a second photoelectric signal converter, a spread spectrum demodulator, a second spreading code generator, a signal demodulator, a camera and a display screen. With the system adopted, the locations of the vehicles can be obtained by means of the optical signals of the street lamps and the positioning data of nearby vehicles.

The invention relates to an Internet of vehicles and things-based vehicle positioning system. The system is characterized in that the system includes a vehicle and a plurality of street lamps arranged at roadsides; each street lamp is provided with a memory which stores street lamp geographic locations, a signal modulator, a first spreading code generator, a spreading modulator, a first photoelectric signal converter and an LED light source; a plurality of square LED emitting light lattices which are independently numbered are uniformly arranged in the LED light source; black light LEDs, blue light LEDs, green light LEDs and red light LEDs are arranged in the LED emitting light lattices; the vehicle is provided with a central processor, a speed detector, a GPS positioning module, an optical signal intensity detector, an optical signal receiver, a second photoelectric signal converter, a spreading demodulator, a second spreading code generator, a signal demodulator, a camera and a display screen; the street lamp geographic locations are converted into optical signals and multidimensional color codes from electric signals; and the central processor completes the final positioning of the vehicle according to GPS positioning signals, vehicle speed and the optical signal intensity of each street lamp.

The invention provides a power cable partial discharge positioning method. The method comprises the steps that S1 a partial discharge signal of a test cable is acquired, wherein the partial dischargesignal comprises an incident wave signal and a reflected wave signal; S2 the acquired partial discharge signal is decomposed; when the number of times of decomposition is equal to the set number of decomposition layers, the decomposition is stopped; a sub-band signal corresponding to the number of times of decomposition is acquired; S3 the kurtosis of the sub-band signal is calculated, and a firstsub-band signal whose kurtosis is greater than a set kurtosis threshold is acquired; S4 the wavefront position propagation time difference of the incident wave and the reflected wave of each first sub-band signal and the wave velocity corresponding to the center frequency are calculated respectively; S5 according to the propagation time difference and the wave velocity, the partial discharge position of each first sub-band signal is acquired; and S6 the final partial discharge position is acquired according to the partial discharge position of each first sub-band signal. According to the invention, the accuracy of partial discharge positioning can be improved.

The invention discloses a low-temperature radiometer black cavity light beam alignment device and method and belongs to the field of light radiation power measurement. The device includes an off-axisparaboloidal mirror, an off-axis paraboloidal mirror base, a low-temperature radiometer black cavity, a four-quadrant detector, a direct-current amplifier and a thermal insulation base. The off-axis paraboloidal mirror is mounted on the off-axis paraboloidal mirror base; the center of the mirror surface of the off-axis paraboloidal mirror is provided with an off-axis paraboloidal mirror central hole; the off-axis paraboloidal mirror is coaxially mounted with the low-temperature radiometer black cavity and closely fits the low-temperature radiometer black cavity, and the four-quadrant detectoris mounted on the thermal insulation base. Since the off-axis paraboloidal mirror is coaxially mounted with the low-temperature radiometer black cavity, when a light beam is adjusted to the center ofthe mirror surface of the off-axis paraboloidal mirror, it can be ensured to the maximum degree that the light beam can be maintained at the axial position of the low-temperature radiometer black cavity and normal incidence of the light beam is achieved; a laser beam entering a low-temperature radiometer is a linearly polarized collimated light beam which is subjected to spatial filtering, so thatthe quality of the light beam is excellent, and there is less stray light.

A silk-screen printing fixture comprises a bottom plate and a pressing mechanism, wherein a cavity which can be in clearance fit with a to-be-printed piece is formed in the bottom plate; the bottom plate comprises a first inner wall and a second inner wall which are opposite; a slide way groove is formed in the first inner wall; the pressing mechanism is glidingly arranged in the slide way groove and is propped against the to-be-printed piece; and the pressing mechanism tightly presses the to-be-printed piece and tightly attaches the side surface of the to-be-printed piece to the second inner wall. When the silk-screen printing fixture is required for printing patterns, such as a window or keys and the like, on the to-be-printed piece such as a piece of glass of a cover plate of a mobile phone, the to-be-printed piece is placed in the cavity formed in the bottom plate, and the pressing mechanism tightly presses the to-be-printed piece to the second inner wall opposite to the first inner wall, so that the influences of fit clearance on positioning of the to-be-printed piece is reduced, the fit clearance between the silk-screen printing fixture and the to-be-printed piece can even be eliminated, the positioning accuracy of the window, the patterns and the like of the to-be-printed piece is improved, and accurate positioning is realized.

The invention provides a positioning method, a positioning system and a nonvolatile computer readable storage medium. The positioning method provided by the embodiment of the invention comprises the following steps: acquiring a look-around image of a current scene; acquiring current scene information, current road feature information and current obstacle information according to the look-around image; matching with an existing virtual map according to the current scene information, the current road feature information and the current obstacle information to obtain positioning information; andoutputting the positioning information. According to the positioning method, the positioning system and the nonvolatile computer readable storage medium of the embodiment of the invention, the currentscene information, the current road characteristic information and the current obstacle information in the look-around image are identified to be matched with the existing virtual map; during positioning, various environmental factors are matched, so that the influence of the environmental factors on positioning is reduced, and the positioning precision is improved.

The invention discloses a goods positioning method, a device, a system and a computer readable storage medium. The method comprises the steps: collecting an image of a to-be-positioned goods, carryingout the segmentation of the collected image through an ordered point cloud, and obtaining a to-be-positioned image; inputting a to-be-positioned image into the image positioning model to obtain an angular point segmentation image and a position sensitive segmentation image corresponding to the to-be-positioned image; and based on the image positioning model, determining the position of the to-be-positioned goods according to the corner segmentation map and the position sensitive segmentation map. According to the invention, the collected image is segmented through the ordered point cloud, theobtained to-be-positioned image is input into the image positioning model, and the position of the to-be-positioned goods is determined according to the angular point segmentation image and the position sensitive segmentation image output by the image positioning model, so that the goods positioning stability and the goods recognition rate are improved.

The invention is suitable for the medical instrument technology field, and discloses a hand-operated minimally invasive spinal column operation guiding device. The guiding device comprises a vertical main body support bar, a vertebra fixing mechanism two ends of which extend out of the main body support bar and one end is fixed on the vertebra of a patient, an adjusting mechanism that is arranged at one end of the main body support bar and is used for hand-operated adjusting, and a guiding mechanism arranged at the end of the adjusting mechanism for position and posture adjustment with the help of the adjusting mechanism. The vertebra fixing mechanism can be fixed directly on a patient's spinal column, therefore, influence of spinal column follower generated by physiological respiratory movement to positioning is reduced and operation precision is improved; by hand-operated adjusting, influence of power off during the operation and other emergent events to the operation is avoided, thereby guaranteeing operation security; by arranging the adjusting mechanism, pedicle nail channel position and attitude adjusting at different vertebra segments can be realized, and operation guiding is provided by arranging the guiding mechanism.

The invention discloses a self-adaptive real-time multipath elimination and robust positioning method based on non-Gaussian distribution. The method does not assume the number of satellites with faults or deviations, but modifies the Gaussian distribution assumption of errors in a traditional positioning model, and changes the Gaussian distribution assumption into Gaussian mixture distribution, namely non-Gaussian distribution. Parameters are solved through a maximum likelihood method based on real-time observation data, the probability distribution situation of the fault deviation range of each satellite is calculated in a self-adaptive mode, and the method can be used for recognition and robust positioning under multiple faults and can also be used for robust positioning and multipath elimination under the multipath environment. According to the method, the defects of an existing RAIM and robust positioning method are overcome, an existing fault detection and recognition method at present is large in calculation amount, depends on the prior assumption of the number of faults and is high in misjudgment rate, and the method has the high fault detection success rate, meanwhile, the calculation amount is small, the speed is high, and high precision and robustness are achieved.

The invention relates to a sliding window profile and a mounting method thereof. The sliding window profile comprises a concentric-square-shaped frame, wherein mounting grooves are formed in the outerwalls of the periphery of the frame in the circumferential direction of the frame; air bags are arranged in the mounting grooves, an air inlet end opening and an air outlet end opening which communicate with the air bags are formed in the frame, and sealing pieces used for opening and closing the air inlet end opening and the air outlet end opening are arranged on the frame; and turning plates are rotationally arranged on the outer walls of the periphery of the frame, and the movable ends of the turning plates are arranged in the mounting grooves. When a constructor installs the frame, the frame is firstly placed at a proper position in a window, then an inflator is used for inflating the air bags, the air bags in all directions of the frame are evenly bulged, the turning plates are ejected out of the mounting grooves of the frame in the expansion process of the air bags and abuts against the window, and the frame is automatically positioned when the air bags expand, so that the frameis pre-fixed. The sliding window profile and the mounting method thereof have the effects that the frame positioning work is rapid and labor-saving, and the positioning is accurate.

The invention discloses a multi-robot cooperative positioning method based on UWB and IMU fusion, and relates to the technical field of indoor positioning. Acquiring predicted coordinates of the target robot and other robots through IMU modules of the target robot and other robots, and calculating the distance between the target robot and other robots as a first distance; taking the UWB module of the target robot as a positioning label, taking the UWB modules of other robots as positioning base stations, and measuring the distance between the target robot and other robots as a second distance; determining a target distance according to the second distance and the first distance corresponding to the second distance; and determining position information of the target robot according to the plurality of target distances and a preset positioning algorithm. The UWB module of the robot is used as a positioning base station, the positioning range can be flexibly changed along with the movement of the robot, and the actual measurement distance and the estimated distance are used for positioning, so that the influence of NLOS on positioning is reduced.

The present disclosure provides a robot positioning method, device and robot, which relate to the field of robot technology, wherein the method includes: determining the positioning grid corresponding to the detected obstacle in the two-dimensional grid map; obtaining the positioning grid and the distance from the positioning grid The first distance between the nearest obstacle grids; determine whether the first distance is greater than the preset distance threshold, if yes, determine that the detected obstacle corresponding to this positioning grid is a dynamic obstacle, if not, determine The detected obstacles corresponding to the positioning grid are static obstacles; the robot is positioned based on the detected obstacles determined to be static obstacles. The robot positioning method, device and robot of the present disclosure can filter out dynamic obstacles that do not exist in the map according to the shortest distance to obstacles and the distance mapping map, and reduce the impact of dynamic obstacles in the environment on positioning, and can Enhance the accuracy and stability of robot positioning.

The invention relates to an indoor positioning method based on improved WKNN, and the method comprises the following steps: fencing and determining reference points in a positioning area, selecting an AP set suitable for subsequent positioning according to RSS of APs collected in the reference points, and storing related data in a fingerprint database. recording RSS of an AP of a positioning point by using a portable device, judging a positioning area according to the same Mac address, selecting reference points similar to the numerical value change trend of the positioning point AP according to the quantity difference of wave crest and wave trough values between the positioning point and the reference points, selecting K reference points with the minimum Euclidean distance through a KNN algorithm, giving weights through normalization and a wasserstein distance, judging whether the reference points are similar reference points or not, giving weights, and obtaining a final result through weighted averaging.