4results about How to "Excellent path" patented technology

The application discloses a kind of based on task partition's shipborne unmanned aerial vehicle navigation beacon group path planning method, belong to offshore navigation beacon inspection technical field.The method first obtains navigation beacon, mother ship, obstacle and unmanned aerial vehicle constraint parameter, is divided into navigation beacon by recursion K-means and is checked by threefold verification of operation radius, load, endurance, and is recursively subdivided if unqualified;Second generation mother ship candidate residence point and correct to safe water area, use A* algorithm to plan the global transfer path of mother ship, model as closed loop traveling salesman problem in cluster inspection, to improve self-organizing mapping neural network is solved unmanned aerial vehicle path in combination with tabu search.The system contains data input, task partition and the like module.The scheme makes mother ship only stay near task cluster, greatly shortens voyage, reduces risk, improves inspection efficiency and engineering feasibility.

The invention discloses a low-earth-orbit satellite communication network routing method based on reinforcement learning, and relates to the field of low-earth-orbit satellite communication networks in 5G NTN, in particular to the low-earth-orbit satellite communication network routing method based on reinforcement learning. The objective of the invention is to solve the problem that existing reinforcement learning Q-Learning applications are mostly focused on a ground network, and the unique dynamic topology and three-dimensional space routing problems of a satellite network are not solved. The invention provides a lightweight and adaptive low earth orbit satellite communication network routing optimization method based on reinforcement learning. The method is realized through distributed Q-Learning: dynamically adapting to topological change, dynamically adapting to three-dimensional space routing, balancing link load, minimizing end-to-end delay, and reducing on-satellite computing overhead.

This application provides an optical system and a laser cutting device. The system includes a first focusing lens, a concave lens, and a focusing lens group arranged coaxially along a first direction. The first direction is the initial transmission direction of the light emitted by the target light source. The optical axis of the first focusing lens passes through the virtual focal point of the target light source. The virtual focal point is the point where the reverse rays of the light emitted by the target light source converge. The distance between the first focusing lens and the virtual focal point of the target light source is greater than the focal length of the first focusing lens. The concave lens is configured to change the distance between itself and the first focusing lens to adjust the aberration of the light emitted by the target light source. As the distance between the first focusing lens and the concave lens in the collimating lens group changes from far to near, the optical system exhibits the following trends: negative defocus beam convergence and tending towards a flat top, positive defocus dispersion and tending towards Gaussianization, then the distribution of positive and negative defocus beams becomes equal, and finally, negative defocus dispersion and tending towards Gaussianization, and positive defocus beam convergence and tending towards a flat top.

The application discloses a kind of mobile robot global path planning method based on improved mayfly algorithm, comprising the following steps: modeling to map environment;Initialize mayfly population parameters, randomly generate the position of mayfly population, set initial speed, generate initial path, and calculate fitness value;Update the speed and position of male and female mayfly;The fitness value of updated mayfly is calculated and sorted;Generate mayfly offspring, and the mutation operation is carried out to offspring mayfly;The offspring mayfly is divided into male and female, the fitness value of offspring mayfly is calculated, individual optimal, global optimal and related parameters are updated;Update dance coefficient and random flight coefficient, update weight coefficient;Judge whether to reach maximum iteration number, if yes, then output optimal solution.The application introduces ion motion crossover search rule and adaptive inertia weight to improve the convergence efficiency and global search ability of algorithm, while introducing F distribution random variation to increase the diversity of algorithm search result, and convergence process is more rapid and stable.