6results about How to "Keep track" patented technology

The invention relates to the technical field of image processing and machine vision, in particular to an anti-occlusion target tracking method integrating Kalman filtering and particle filtering, which is low in cost, low in complexity, high in real-time performance and high in stability, and compared with the prior art, the robustness and the accuracy of a target tracking algorithm in an occlusion scene can be remarkably improved, and the target tracking method has the advantages of high robustness and high robustness. Target tracking loss caused by shielding is effectively avoided; according to the invention, the anti-shielding function is realized only depending on the algorithm, the hardware cost of the system is reduced, and the target tracking algorithm is simpler, more convenient and lighter in engineering application, so that the anti-shielding target tracking method provided by the invention has the characteristics of low cost, low complexity, strong real-time performance and high stability; the target can be continuously tracked in a complex scene, and the method has important application value and wide application prospect.

The invention discloses a low-altitude unmanned aerial vehicle countering monitoring system based on state feature decoding, relates to the technical field of unmanned aerial vehicle prevention and control, and is used for solving the problem of poor low-altitude target detection and countering. According to the invention, through closed-loop management and control of heterogeneous radar networking detection, signal level fusion processing, threat assessment and resource scheduling and intelligent countering decision, accurate identification and directional countering of the low-altitude unmanned aerial vehicle are realized; according to the method, the detection precision and the micro-Doppler feature extraction capability of a low-speed small target are improved by combining a virtual aperture synthesis technology, then unbalanced resource allocation is implemented based on a threat level, the system efficiency is optimized, and finally seamless migration of an interfered node task is realized by constructing a signal interference situation map. And continuous tracking and effect evaluation on the target are maintained in the active radio frequency countering process, so that the overall efficiency and reliability of low-altitude security and protection in a complex environment are effectively improved.

The invention discloses an automatic navigation control system and method of a hydraulic drive crawler, and relates to the technical field of engineering vehicle control, the system comprises a navigation control subsystem used for confirming a starting point and an ending point to confirm a driving path; the man-machine interface logic control subsystem is used for receiving the driving path and setting initial information of the crawler according to the driving path; the crawler driving control subsystem is used for controlling the crawler to run along the running path according to the initial information; the controller is also used for acquiring real-time data and yaw information of the crawler, calculating a yaw distance, comparing the yaw distance with a yaw threshold value to obtain a comparison result, and generating a correction instruction according to the comparison result; and the tracked vehicle driving control subsystem corrects the yawing tracked vehicle based on the correction instruction, so that the tracked vehicle recovers to go straight. According to the method and the device, the crawler running in the preset path can be timely, accurately and automatically corrected.

The utility model discloses a photovoltaic power station support rotating part of automatic lubrication function belongs to photovoltaic power station support technical field, it includes base, the base upper end surface center place is equipped with stand, the stand upper end surface center place is equipped with rotating structure, and the rotating structure includes rotating frame, and the both sides wall center upper of rotating frame is equipped with bearing evenly, and the rotating frame inside center upper is equipped with rotating rod, in addition, the utility model discloses, realize through the linear motion of hydraulic telescopic link efficient stably conversion is driven support main body rotation's circular motion to this adjustment photovoltaic board angle better receive sunlight, has reduced equipment cost, has reduced the precision loss of the intermediate transmission link, just control the telescopic amount of hydraulic telescopic link, can accurate control rotating frame and support main body's rotation angle, guarantee photovoltaic board can continuously track sunlight, effectively improve power generation efficiency.

The application discloses a pig farm disease risk prediction method, system and platform based on a small sample scene, and the method is used for acquiring original record data corresponding to pig farm diseases in real time, and determining and generating pig farm disease record data corresponding to a small sample scene; a corresponding knowledge fusion model is constructed according to the pig farm disease original record data in the small sample scene, and early warning data corresponding to the pig farm diseases is generated in real time in combination with the knowledge fusion model; a corresponding risk point identification model is constructed, and pig farm disease risk prediction data corresponding to the early warning data is generated in real time according to the risk point identification model, which can assist front-line pig farm managers to achieve early discovery, accurate positioning, timely prevention and control and continuous tracking. Through risk early warning, intervention measures such as immunization, disinfection and purification are carried out on potential pig farms in time, so that the abortion rate and the stillbirth rate of the pig farms are reduced, and economic losses are avoided.

This application relates to a method for training a Conditional Variational Autoencoder (CVAE) network. The method includes: Step A: using scene information and the recorded trajectory of a target vehicle as input to the CVAE network, wherein the scene information is a conditional vector and the recorded trajectory of the target vehicle is a sample vector; and wherein the CVAE network includes: an encoder for compressing the sample vector along with the conditional vector into a low-dimensional vector z, wherein the low-dimensional vector z is a latent variable following a standard normal distribution; and a decoder for generating new samples as output based on the low-dimensional vector z, wherein the new samples represent the predicted trajectory of the target vehicle. This application also relates to a method for evaluating a CVAE network, a method for adaptive cruise control, a computer program product, and a domain controller.