Unmanned aerial vehicle static and dynamic path planning method based on digital map

Abstract

The invention provides an unmanned aerial vehicle static and dynamic path planning method based on a digital map, and relates to the technical field of unmanned aerial vehicle path planning. The method comprises the steps of: constructing an unmanned aerial vehicle flight three-dimensional digital map; setting initial and end position coordinates of flight of an unmanned aerial vehicle, and initializing an unmanned aerial vehicle path planning constraint condition; according to a hybrid particle swarm simulated annealing algorithm, updating a speed and positions of particles; drawing an unmanned aerial vehicle global static optimal flight path; judging whether the unmanned aerial vehicle encounters an emergent threat, and if yes, according to the hybrid particle swarm simulated annealing algorithm, re-planning a static flight path; and drawing an unmanned aerial vehicle global dynamic optimal flight path. By the method, in a static case, an accurate global flight track can be rapidly planned; and in a case of the emergent threat in the flight process, the threat can be rapidly avoided to effectively carry out path re-planning so as to guarantee flight safety of the unmanned aerialvehicle.

Description

technical field [0001] The invention relates to the technical field of UAV path planning, in particular to a digital map-based static and dynamic path planning method for UAVs. Background technique [0002] UAV (Unmanned Aerial Vehicle, UAV) is called an unmanned aircraft, which flies by receiving radio instructions or controlled by its own program. In the 20th century, the first unmanned aerial vehicle was successfully developed, and then the unmanned aerial vehicle in the form of a target aircraft was successfully developed. Successful research and development have played their respective roles in different fields. With the rapid development of science and technology in today's society, especially in the modern battlefield environment, unmanned military equipment has become an obvious trend. With the continuous improvement of aviation flight technology, the military value of drones with autonomous control functions on the battlefield is becoming more and more obvious. Th...

AI Technical Summary

Problems solved by technology

Usually, there are many uncertain factors in the flight environment of UAVs, which makes it impossible to obtain accurate global flight environment information at the initial stage. Therefore, the traditional static global path planning of UAVs cannot achieve real-time combat of current UAVs. Require

At present, the dynamic path planning of UAVs generally chooses to bypass the sudden threat and then return to the original static planning route when encountering a threat. This processing method will not only increase the path re-planning time, but also increase the path cost, which in turn increases fuel consumption and poor maneuverability

[0004] In recent years, the research focus of path planning is mainly on the UAV path planning search algorithm based on geometry, which is mainly divided into random search algorithm and deterministic search algorithm. Among them, the deterministic search algorithm includes dynamic programming algorithm, D* Algorithm, A* algorithm, and Dijkstra algorithm, these algorithms are predictable for path search, the requirements for model establishment are relatively simple, and it is easy to solve the problem. The amount of data calculation is relatively large, and the combination explosion will occur when using the deterministic algorithm, which is not conducive to solving the path planning problem, while the random search algorithm has better global optimization performance in complex problem spaces, and its robustness and parallelism Compared with the deterministic search algorithm, it has obvious advantages

However, the current flight environment is becoming more and more complicated, and the flight requirements for UAVs are also getting higher and higher. Challenging subjects

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