7results about How to "Reduce positioning impact" patented technology

The invention discloses a camera inclination angle calibration method based on high-precision thermocompression bonding equipment, and the method comprises the following steps: 1, enabling the installation angle of a camera to be parallel to a reference plane through adjusting the installation angle of the camera; 2, adjusting the inclination angle of the camera mounting angle relative to the reference plane within a set range along the X direction, wherein one unit inclination angle is adjusted each time; the average value is calculated, the leveling value serves as the proportion value Xp of the current inclination angle to the inclination angle in the X-axis direction, and therefore a curve of each inclination angle pair in the X-axis direction and the corresponding proportion value Xp in the set range is obtained; adopting the same method to obtain a curve of each inclination angle pair and the corresponding proportion value Yp in the set range along the Y direction; and 3, carrying out linear fitting on the curve of the proportion value Xp and the curve of the proportion value Yp to obtain a linear relationship between the inclination angle of the camera and the proportion value Xp and the proportion value Yp so as to realize calibration of the inclination angle of the camera.

The invention relates to a satellite map matching and positioning method and device based on a road similarity space. The method comprises the following steps: firstly, constructing a data acquisition system to generate a local aerial view of multi-modal space-time fusion, and then generating a global satellite road similarity map and a BEV road similarity map through road similarity analysis. The initial position of the unmanned vehicle is determined through comparison of a local aerial view and an initial satellite area, an initial BEV sensing result is obtained, a scanning matching strategy is adopted to be matched with a global satellite road similarity map, a matching degree score matrix around the initial position is obtained, and the highest score position is selected as a posterior position. A current priori position is obtained from a posterior position of a previous moment in combination with a relative motion amount predicted by a speedometer, a current BEV road similarity graph and a corresponding satellite similarity graph block are scanned and matched at the current priori position, a current matching degree fractional matrix is obtained, and finally a satellite image map matching result is obtained according to a particle filtering algorithm and the matrix. By adopting the method, the satellite image matching and positioning accuracy can be improved.

This invention relates to the field of remote positioning technology for small devices, and discloses a method and system for remote positioning of Bluetooth devices based on the Internet of Things (IoT). The method includes: acquiring initial signal data emitted by the Bluetooth device to obtain classified signal strength groups; obtaining a subset of signal data based on the degree of environmental interference and preset screening conditions; extracting relevant feature data to obtain a signal distribution feature set, performing time delay deviation calibration and matrix processing to obtain a signal data matrix; extracting initial feature values ​​to determine the weighted signal data weight distribution; prioritizing the signals to obtain an optimized signal data combination; obtaining the final positioning network topology based on the signal data combination and signal strength threshold; and performing iterative calculations based on the positioning network topology to obtain the final location information of the Bluetooth device. This method enables accurate positioning of Bluetooth devices in dynamic and complex environments.

The application discloses a vehicle positioning estimation method, which comprises the following steps: obtaining an initial pose satisfying a switching condition based on a particle filter algorithm; fusing the initial pose of the vehicle satisfying the switching condition, laser point cloud data and wheel odometer data based on an unscented Kalman filter algorithm to estimate the pose of the vehicle and obtain vehicle pose estimation data; calculating the variance of the current pose state estimation to determine whether the current pose is reliable; if the current pose is reliable, updating the current pose as the current pose estimation data and estimating the pose state of the next state of the vehicle based on the unscented Kalman filter; and if the current pose is not reliable, estimating the pose state of the next state of the vehicle based on the particle filter algorithm. The application further discloses a corresponding system, a storage medium and a vehicle. When the positioning estimation is performed, the application can break the dependence on the third source input of the initial pose of the vehicle, and improve the positioning accuracy and stability of the vehicle in a complex nonlinear scene.

The invention relates to a training method, an audio-visual segmentation method, an electronic device and a storage medium, and the method comprises the steps: obtaining a training sample which comprises an audio signal, an image, a target semantic tag and a segmentation tag; extracting audio features and image features, and performing self-attention enhancement on the audio features based on the target semantic tag to apply target semantic consistency constraint to obtain enhanced audio features; performing cross attention reweighting on the unenhanced audio features based on the guidance of the enhanced audio features to obtain target pointing audio features; bidirectional interactive fusion is executed based on the image features and the target pointing audio features, and a sparse self-attention network is adopted in the image feature fusion process to suppress unmatched image region response; generating a segmentation prediction result based on the fused image features and audio features, and training to obtain an audiovisual segmentation model; and inputting a to-be-processed video into the trained audio-visual segmentation model, and outputting a segmentation result. The image segmentation accuracy of the sounding target can be improved.

The invention discloses a dynamic map construction and block differentiation updating method, which comprises the following steps of: dividing a map into four types of map blocks, namely stable blocks, slow change blocks, low dynamic blocks or ground blocks, and endowing different positioning weights and updating strategies for each type of map blocks; the map block type is dynamically adjusted through a change rate detection algorithm, and self-adaptive map management is achieved. According to the method, the robustness of positioning registration is improved, the interference of dynamic objects is reduced, the classified management and differentiated updating of map blocks are realized, the long-term reliability and accuracy of the map are ensured, and meanwhile, the dynamic loading and efficient updating of an infinite map are supported.

This utility model relates to crack detection and discloses a crack width measuring instrument, including a measuring instrument body, a probe communicatively connected to the measuring instrument body, and a detachable positioning component mounted on the measuring instrument body. The positioning component includes a mounting part and a positioning block. The mounting part is snapped onto the outer periphery of the measuring instrument body. Multiple fixing seats and snap-fit ​​seats are arranged opposite each other on the side edge of the mounting part away from the measuring instrument body. The snap-fit ​​seats are provided with mounting grooves and snap-fit ​​doors. A rotating rod is provided on the side of the positioning block. Both ends of the rotating rod are inserted into the fixing seats and the mounting groove, respectively. When the snap-fit ​​door is closed, it is used to fix the rotating rod. The positioning block also has mounting holes, and the probe is detachably connected to the mounting holes. This utility model can adapt to crack measurement in different directions without frequent adjustments to the position of the measuring instrument body.