Three-dimensional flight path planning method and device for unmanned aerial vehicle

Abstract

The invention provides a three-dimensional flight path planning method for an unmanned aerial vehicle. The method comprises the following steps: constructing a three-dimensional terrain environment model, a flight path evaluation model and a flight path optimization constraint model; constructing a cell membrane structure; performing track search space discrete reduction and parameter initialization setting; searching an optimal track point; and performing track smoothing processing. According to the method, the global search capability of FA and the local search capability of ABC are combined, the overall search performance is enhanced, and the search probability and real-time performance of a three-dimensional flight path constructed by the method are remarkably improved; meanwhile, theinvention further provides a three-dimensional flight path planning device for the unmanned aerial vehicle, and the device comprises a cell membrane unit, a power supply unit, a clock unit, an EEPROMand an SRAM.

Description

technical field [0001] The invention belongs to the technical field of aircraft track planning, and in particular relates to a three-dimensional track planning method and a track planning device for an unmanned aerial vehicle. Background technique [0002] The rapid development of unmanned aerial vehicle (UAV, Unmanned Aerial Vehicle) technology and its application advantages have made UAV systems widely used in military / civilian fields. Among the many key technologies of the UAV system, the role of trajectory planning is to search for a feasible trajectory between the starting point and the target point that not only satisfies the physical properties of the UAV itself, but also avoids external environmental threats. Especially in the military field, efficient optimized trajectory can affect the survival and mission performance of UAVs. [0003] Wang Qiong pointed out in the document ""A Review of Commonly Used Algorithms for UAV Track Planning", Journal of Jilin University...

AI Technical Summary

Problems solved by technology

Intelligent optimization algorithms have achieved good results in solving the problem of trajectory planning, but algorithms such as particle swarms, genetics, ant colonies, and bee colonies have premature convergence problems, and cannot simultaneously search for local optimal values ​​and explore the gap between global optimal values. balance, so that the trajectory planning is easy to fall into the local optimal solution and difficult to obtain the global optimal path

In addition, the intelligent optimization algorithm is applied to three-dimensional track search, because of the increase of height information, the search dimension becomes larger, the amount of search data is significantly higher than that of two-dimensional track search, and its real-time performance is correspondingly worse

[0005] It can be seen that the above-mentioned intelligent optimization method is obviously insufficient for UAV three-dimensional track planning, and is not suitable for UAV track planning with strong real-time performance. Research on new three-dimensional track planning methods with strong real-time calculation has become a key technology for the development of UAV applications. one

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