UAV path optimization method based on improved bidirectional fast expanding random tree algorithm

A path optimization and random tree technology, applied in computing, machine learning, computing models, etc., can solve the problems of UAV path planning efficiency, poor and other problems, reduce random point expansion, improve trend, and improve convergence speed. Effect

Active Publication Date: 2021-11-16
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 random tree algorithm, which solves the problem that the B-RRT* algorithm in the prior art cannot be directly used for UAV path planning and poor efficiency The problem

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  • UAV path optimization method based on improved bidirectional fast expanding random tree algorithm
  • UAV path optimization method based on improved bidirectional fast expanding random tree algorithm
  • UAV path optimization method based on improved bidirectional fast expanding random tree algorithm

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[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 two-way rapid expansion random tree algorithm. The method includes the following steps: 1. Establishing a UAV kinematics constraint model and determining a starting point and a target point in a two-dimensional space; 2. Extend the nodes of the bidirectional random tree based on the backward fan-shaped area sampling method; 3. Solve the problem of growth limitations near obstacles based on the dynamic adaptive step size method; 4. Form a complete bidirectional search tree by connecting the nodes flight path. Based on the classic B-RRT* algorithm, the present invention is based on the backward fan-shaped area sampling method. When the node expands, the random tree sampling points are limited to the backward fan-shaped area. The problem of the growth limitation in the vicinity, and finally connect each node to generate a flight path that conforms to the real flight path of the UAV, which provides a feasible method for the autonomous navigation flight 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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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06N20/00G01C21/20
CPCG01C21/20G06Q10/047
Inventor 沈志远赵帅卢朝阳
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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