UAV path optimization method based on improved bidirectional rapidly-exploring random-tree algorithm

A path optimization and random tree technology, applied in the direction of calculation, calculation model, navigation calculation tools, etc., can solve problems such as poor path planning efficiency of drones, to improve tendency, reduce random point expansion, and improve convergence speed Effect

Active Publication Date: 2018-10-19
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a UAV path optimization method based on the improved two-way rapid expansion rando

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  • UAV path optimization method based on improved bidirectional rapidly-exploring random-tree algorithm
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  • UAV path optimization method based on improved bidirectional rapidly-exploring random-tree algorithm

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Embodiment Construction

[0038] Embodiments of the invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0039] Such as figure 1As shown, it is a flow chart of the UAV path optimization method based on the improved bidirectional fast expanding random tree algorithm of the present invention. Including the following steps:

[0040] Step 1. Establish the kinematic constraint model of the UAV, and under certain conditions, simplify the actual task of the UAV, and determine the starting point and target point in the two-dimensional space;

[0041] According to the space environment and threat parameters of the mission area, the UAV is required to plan a feasible trajectory from the current planning starting point to the target point without collision, which needs to meet the f...

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Abstract

The invention discloses a UAV path optimization method based on an improved bidirectional rapidly-exploring random-tree algorithm. The method comprises the following steps: 1, establishing a UAV kinematic constraint model and determining a starting point and a target point in a two-dimensional space; 2, based on a backward sector region sampling method, exploring the nodes of the bidirectional random tree; 3, based on a dynamic adaptive step size method, solving the growth limitations near an obstacle; and 4, by connecting the nodes of a bidirectional search tree, forming a complete flight path. Based on a classical B-RRT* algorithm, the method, based on the backward sector region sampling method, restricts random tree sampling points to the backward sector region when the nodes are explored, solves the growth limitations near the obstacle based on the dynamic adaptive step size method, and finally connects respective nodes to generate a flight path that conforms to the real flight ofthe UAV, thereby providing a feasible method for autonomous navigation of the UAV at low altitude.

Description

technical field [0001] The invention relates to an unmanned aerial vehicle path optimization method based on an improved two-way rapidly expanding random tree algorithm, and belongs to the technical field of autonomous navigation flight and operation safety guarantee of unmanned aerial vehicles at low altitudes. Background technique [0002] With the advancement of electronic information technology and the development of science and technology, the UAV (Unmanned Aerial Vehicle) has the advantages of small size, low cost, high efficiency, no casualties, strong survivability, good maneuverability, and convenient use. increasingly favored by countries. And the use of drones has expanded from the military field to the civilian field. With the rapid development of the military and civilian UAV market, considering that there are many types of UAVs and their tasks are also different, it is necessary to plan the path of each UAV. With the gradual liberalization of low-altitude air...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N99/00G01C21/20
CPCG01C21/20G06Q10/047
Inventor 沈志远赵帅卢朝阳
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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