7results about How to "Improve mapping accuracy" patented technology

This invention discloses a video tag dynamic overlay anti-shake method and system based on AR, comprising: acquiring real-time video stream and device pose parameters at corresponding timestamps; constructing a dynamic perspective projection model based on the device pose parameters and calculating the initial pixel coordinates of the target AR tag in the current video frame; planning a local feature search window based on the initial pixel coordinates; calculating the average pixel displacement vector of image feature points in the local feature search window of the current and adjacent historical video frames; performing reverse displacement compensation on the average pixel displacement vector to obtain the target rendering coordinates, and rendering the target AR tag to the current video frame based on the target rendering coordinates. Compared with the prior art, this invention can overcome the shortcomings of large drift errors caused by simply relying on mechanical pose, high computational power consumption caused by global matching, and high-frequency jitter of tags caused by slight device vibrations, thereby improving tag mapping accuracy, reducing system computational power consumption, and improving the visual stability of video overlay.

The application discloses a robot map updating method, which comprises the following steps: step 1, a robot establishes a current map in a current environment; step 2, the current map is updated according to the angle relationship between the current map and a map stored in a historical map library last time, the updated current map is stored in the historical map library, and the updated current map is updated as the map stored in the historical map library last time, so that the current map established in step 1 is updated; wherein each frame of map stored in the same historical map library represents the current environment.

This utility model discloses an irregularly shaped foldable three-axis drone frame and drone device, comprising: an assembly frame structure; a front rotor assembly structure, comprising two sets, the two sets of front rotor assembly structures being respectively and positionably interchangeably mounted on the front two sides of the assembly frame structure, and the rotation directions of the driving rotation ends of the two sets of front rotor assembly structures being opposite to each other; and a rear rotor assembly structure, comprising a single set, extending to the rear of the assembly frame structure, the rear rotor assembly structure having two sets of coaxially arranged driving rotation ends, the two sets of driving rotation ends being opposite to each other. This solves the technical problem in the prior art where drone frames struggle to simultaneously achieve portability and field of view advantages.

This invention relates to an artificial intelligence-based control method and system for retractable roof greenhouses used in peach tree cultivation, specifically as follows: First, an IoT sensor network is deployed to collect greenhouse environmental data and label growth stages, defining optimization tasks and action spaces. After aligning multi-source data using a dynamic time warping algorithm, environmental features and agricultural operations are fused using tensor decomposition technology. Constraint-aware convolution is used to embed environmental constraints and extract features, combining photosynthetically active radiation utilization rate and sensitivity indicators to obtain a growth efficiency feature vector. A strategy network is constructed through stage-adaptive exploration, bi-branch value function calculation, constraint-enhanced action selection, and deterministic strategy gradient optimization, ultimately outputting control commands to drive the greenhouse equipment. This method can accurately quantify the impact of environmental factors, improve the safety and effectiveness of control, and adapt to the growth needs of peach trees.

This application discloses a camera calibration method, apparatus, electronic device, and storage medium. The method includes acquiring multiple corresponding point pairs between 2D points in an image captured by a roadside camera and 3D points in a real roadside scene to obtain a first calibration parameter. The 3D points include coordinate position points in a world coordinate system, and the 2D points include coordinate position points in a pixel coordinate system corresponding to the 3D points. The first calibration parameter is iterated according to a preset optimization function to obtain a second calibration parameter. The mapping relationship table between the 2D points and 3D points is determined according to the second calibration parameter. This application improves the 2D-3D positioning accuracy of the roadside camera by optimizing and iteratively calculating the extrinsic parameter matrix.

The utility model discloses an unmanned plane aerial surveying and mapping device relates to unmanned plane technical field, the utility model discloses an unmanned plane body, the unmanned plane body bottom is provided with surveying and mapping camera, the unmanned plane body bottom is provided with automatic leveling mechanism, and the automatic leveling mechanism includes the installation shell of setting in the unmanned plane body bottom, the rotating stand of fixed connection in the installation shell top, and the counterweight of fixed connection in the installation shell one side. The utility model discloses through the cooperation of automatic leveling mechanism and counterweight, can dynamic adjustment surveying and mapping camera's horizontal state in the unmanned plane flight process, ensures that the picture always is perpendicular to the ground, effectively reduces image tilt and distortion, significantly improves surveying and mapping precision, and the airbag, catheter and check valve design in the stop gear, can buffer swing in the leveling process, prevent the shaking caused by gas backflow, further enhance the stability of camera in dynamic adjustment.

This invention relates to the field of industrial internet technology and discloses a dynamic optimization control method for industrial internet production lines based on digital twins. The method includes the following steps: S1, constructing a synchronous mapping twin to generate a digital twin mapped to the physical production line; S2, building a dynamic optimization model to construct a control model integrating deep reinforcement learning and adaptive fuzzy logic; S3, embedding predictive maintenance feedback; S4, performing virtual-real interaction verification; and S5, constructing a twin interaction platform. This invention, through an improved attention mechanism deep learning model in S1, introduces dynamic allocation of data fusion weights to control strategy influence factors, enhancing the accuracy of key data feature extraction. After feature mapping and weighted fusion of multi-source heterogeneous data, the resulting global feature tensor accurately reflects the core state of the production line, solving the problem of key information being submerged in traditional data fusion, providing high-quality data support for subsequent optimization control, and improving the mapping accuracy between the digital twin and the physical production line.