Unmanned aerial vehicle path planning method based on adaptive weight pigeon flock algorithm
A technology of adaptive weight and route planning, which is applied in the direction of navigation calculation tools, etc.
Active Publication Date: 2017-02-22
SHENYANG AEROSPACE UNIVERSITY
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Problems solved by technology
[0006] The existing pigeon swarm algorithm cannot accurately plan the route for complex terrain in solving the UAV route planning problem. To solve this problem, the pigeon swarm algorithm is improved, and the pigeon swarm algorithm with adaptive weight is used to calculate and solve the route. The optimal waypoint in the planning problem, and use the mathematical model to perform path smoothing calculation operations on the sought waypoint
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Embodiment 1
[0070] Through a series of experiments, the feasibility and effectiveness of the improved adaptive pigeon swarm algorithm are demonstrated, and the improved adaptive weight pigeon swarm algorithm (AWPIO) is compared with the original pigeon swarm algorithm (PIO) and particle swarm algorithm (PSO). ) Respectively carried out comparative analysis;
[0071] The simulation experiment part of the entire UAV route planning uses the Matlab R2016 platform in the Windows7 operating system for threat modeling and route simulation. The hardware configuration is: Intel i5-2400@3.10GHz processor, 4GB memory, which uses a geographical range of 80*110km, and each unit length in the coordinate system represents a distance of 1km. The threat source distribution is set according to the planned area The threat factor and other data of the threat source are shown in Table 1. The coordinates of the starting point in the set threat environment area are (14, 10), and the coordinates of the target point...
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The invention relates to an unmanned aerial vehicle path planning method, in particular to an unmanned aerial vehicle path planning method which is based on an adaptive weight pigeon flock algorithm, and belongs to the field of artificial intelligence. The method comprises the following concrete steps: initializing parameters, initializing a path, calculating threat cost, planning the path according to a terrestrial magnetism operator and a landmark operator of an adaptive weight coefficient, and smoothing the path. The adaptive weight pigeon flock algorithm can solve unmanned aerial vehicle path planning problems under different conditions by adjusting parameters in the algorithm, and the parameters can be changed freely according to change of factors such as application fields and constraint conditions of an unmanned aerial vehicle, so that a better planning effect is achieved.
Description
Technical field [0001] The invention relates to an unmanned aerial vehicle route planning method, in particular to an unmanned aerial vehicle route planning method based on an adaptive weight pigeon swarm algorithm, which belongs to the field of artificial intelligence. Background technique [0002] The route planning of unmanned aerial vehicle (UAV) in complex threat environment has been the focus of research by experts and scholars. . The route planning of civil drones needs to consider factors such as the obstruction of urban buildings, the restrictions of the natural geographical environment, and the special weather and climate. Military UAVs also need to always consider the threats caused by the geographical natural environment and local radar signal interference according to the different types of machines they belong to and the different tasks they perform. [0003] The swarm intelligence bionic algorithm is a branch of artificial intelligence, which mainly includes partic...
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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 林娜黄思铭拱长青李席广赵亮
Owner SHENYANG AEROSPACE UNIVERSITY