Three-dimensional route planning method based on improved fruit-fly optimization algorithm
A fruit fly optimization algorithm and route planning technology, applied in the field of robotics, can solve problems such as limited applicability of coding methods and multiple local optima
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2017-08-18
Smart Images

Figure 1 
Figure 2 
Figure 3
Abstract
Description
technical field
[0001] The invention belongs to the technical field of robots, and in particular relates to a three-dimensional route planning method based on an improved fruit fly optimization algorithm. Background technique
[0002] Route planning is a key component of UAV autonomous control. The goal of route planning algorithm is to calculate the optimal or suboptimal flight route for UAV. This flight route can enable UAV to avoid complex terrain obstacles and Penetrate enemy weapons threats and survive yourself while reaching the target point in less time. The UAV 3D route planning problem is a multi-objective and multi-constraint complex optimization problem, which usually has the following characteristics: 1) There are many indicators to evaluate the route performance, and the objective function is difficult to calculate; 2) The battlefield environment is complex and dynamic; 3 ) There are many constraints on the performance of the drone itself; 4) The amount of info...
Examples
Embodiment Construction
[0099] The embodiment of the present invention provides a three-dimensional route planning method based on the improved fruit fly optimization algorithm, which is used to solve the three-dimensional route planning method of the unmanned aerial vehicle under the complex terrain environment and the threat situation of the battlefield by making improvements to the original fruit fly optimization algorithm, The steps are as follows.
[0100] Preparatory work:
[0101] Determine the UAV flight mission information, including the starting point coordinates (x S ,y S ,z S ) T and the end point coordinates (x T ,y T ,z T ) T , the mission map boundary, the number n of route control points that need to be planned;
[0102] Determine enemy ground weapon information, including threat type (radar, missile, anti-aircraft gun), weapon location (x threat j ,y threat j ) T , and their respective threat areas.
[0103] Set the relevant parameters of the improved fruit fly algorithm,...