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Unmanned aerial vehicle route planning method considering arrival time constraint

A technology of arrival time and track planning, applied in three-dimensional position/channel control, non-electric variable control, instruments, etc., to achieve the effect of improving search efficiency

Active Publication Date: 2019-09-20
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0005] The invention discloses a UAV trajectory planning method considering the arrival time constraint. The technical problem to be solved is: according to the actual task requirements, the UAV flight trajectory is obtained based on the specified range sparse A* search algorithm, which has the ability to satisfy complex Advantages of constrained, short-term generation of feasible trajectories

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Embodiment 1

[0072] The simulation hardware is Intel Core i5-6200CPU 2.30GHz, 8G memory, and the simulation environment is MATLABR2016b. UAV formations perform missions in a two-dimensional environment of 10km×10km. The trajectory planning requires the UAV to avoid the no-fly zone in the environment during the process from the starting point to the target point.

[0073] This embodiment discloses a UAV trajectory planning method considering the arrival time constraint, and the specific implementation steps are as follows:

[0074] Step 1: Obtain UAV flight performance parameter information, track constraint information and mission environment information.

[0075] Set the flying speed of the UAV to 35m / s, the maximum turning angle to 90°, and the minimum track segment length l min =1km. The starting point / end point of the drone and the position and radius of the no-fly zone in the mission environment are listed in Table 1. The designated range of the UAV is 9.60km, and the relative error limit...

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Abstract

The invention relates to an unmanned aerial vehicle route planning method considering arrival time constraint, and belongs to the technical field of flight path planning. Aiming at the problem that an unmanned aerial vehicle arrives at a target area at a designated moment, an arrival time constraint model and a flight path planning model are established. On the basis of the SAS algorithm idea, a specified voyage sparse A* search (GRC-SAS) algorithm is provided. In the method, a cost function and a convergence condition of the SAS algorithm are designed, so that a flight path result meets the arrival time constraint; and a node expansion scheme is improved to further improve the search efficiency of the algorithm, so that an unmanned aerial vehicle flight path meeting the constraint is quickly generated. The technical problem to be solved by the invention is as follows: according to the actual task requirement, the unmanned aerial vehicle flight path is obtained based on the appointed voyage sparse A* search algorithm, and the method has the advantages of meeting complex constraints and generating feasible flight paths in a short time, wherein the complex constraints comprise arrival time constraints, unmanned aerial vehicle kinematic constraints and obstacle avoidance constraints.

Description

Technical field [0001] The invention relates to a UAV trajectory planning method considering the arrival time constraint, and belongs to the technical field of trajectory planning. Background technique [0002] In modern warfare, the battlefield environment is complex, and UAVs must meet the requirements of arrival time constraints when performing tasks, and avoid the no-fly zone in the battlefield environment. This is the basis for maximizing combat effectiveness and successfully completing the mission. [0003] In order to meet the UAV arrival time constraints, its processing methods mainly include two types of methods: speed adjustment and range adjustment. The speed adjustment method uses the adjustable range of the UAV's speed to plan the UAV's trajectory to meet the given arrival time constraints. Route planning methods mainly include graph search algorithms (A*, Dijkstra, k optimal path, etc.), numerical optimization algorithms (ant colony optimization, particle swarm optim...

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Application Information

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IPC IPC(8): G05D1/10
CPCG05D1/101
Inventor 龙腾曹严王仰杰王祝
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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