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Multi-unmanned aerial vehicle collaborative target tracking method combining improved APF and segmented Bezier

A multi-UAV, target tracking technology, applied in the control of finding targets, non-electric variable control, instruments, etc., can solve the problems of small calculation amount, algorithm falling into local optimum, path oscillation, etc., to solve the anti-collision problem , to avoid the phenomenon of sharp turns and the effect of preventing large-angle turns

Active Publication Date: 2018-08-14
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

This method is more intuitive and has a small amount of calculation. It is a dynamic path planning method and is widely used in target tracking. However, this algorithm also has problems such as easy to fall into local optimum and path oscillation.

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  • Multi-unmanned aerial vehicle collaborative target tracking method combining improved APF and segmented Bezier
  • Multi-unmanned aerial vehicle collaborative target tracking method combining improved APF and segmented Bezier
  • Multi-unmanned aerial vehicle collaborative target tracking method combining improved APF and segmented Bezier

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Embodiment Construction

[0028] The technical solution of the present invention is described in detail in combination with the accompanying drawings.

[0029] A kind of improved APF of the present invention and subsection Bezier combine multi-unmanned aerial vehicle cooperative target tracking method, specifically comprise the following steps:

[0030] Step 1 Set the size of the environment area, the starting position of the UAV, and the flight step of the UAV. Set the gain coefficients, including target gravitational gain k, obstacle repulsion gain m, and UAV repulsion gain ξ.

[0031] Step 2 uses the airborne camera and lidar to detect the obstacle position, obstacle size and target position.

[0032] Step 3 judges whether j>J (J is the total number of drones), if yes then j=1, go to step 4; otherwise go to step 4.

[0033] Step 4 The jth UAV is at t k Perceive the position of obstacles and targets at all times, and obtain the position of other drones. Calculate the jth UAV at t k target gravit...

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Abstract

The invention discloses a multi-unmanned aerial vehicle collaborative target tracking method combining an improved APF and segmented Bezier. The method comprises the steps that firstly, the position of a target and the position of an obstacle are detected by utilizing an airborne camera and a laser radar; secondly, a model of target gravity and obstacle repulsive force currently borne by unmannedaerial vehicles is established, and a self repulsive force potential field of each unmanned aerial vehicle is built; thirdly, the resultant force borne by the unmanned aerial vehicles is worked out according to the gravity and repulsive force currently borne by the unmanned aerial vehicles, and the unmanned aerial vehicles with paths trapped in local optimum are enabled to escape local optimal points through a virtual obstacle; fourthly, the flight angle of the unmanned aerial vehicles at the next moment is worked out, and next waypoint positions of the unmanned aerial vehicles are calculated;finally, by using a segmented Bezier curve, online smooth optimization is carried out on an air route, optimized next waypoint positions of the unmanned aerial vehicles are obtained, and the steps are repeated till all the unmanned aerial vehicles track the target. The method mainly solves the problem of collisions among the unmanned aerial vehicles in the multi-unmanned aerial vehicle collaborative target tracking process, and meanwhile, the phenomenon of air route oscillation in the tracking process is eliminated.

Description

technical field [0001] The invention belongs to the technical field of multi-UAV cooperative target tracking, in particular to a multi-UAV cooperative target tracking method combining improved APF and segmented Bezier. technical background [0002] Multi-UAV cooperative target tracking refers to the cooperation of multiple UAVs to track the target and avoid obstacles during the tracking process. It is one of the research hotspots in the field of UAV cooperation and cooperation. Value. [0003] There are many methods for multi-UAV cooperative target tracking, which can be divided into two categories: the environment information is completely known and the environment information is unknown. Target tracking and obstacle avoidance methods with fully known environmental information include free space method, Dijkstra algorithm, A* algorithm, etc. Since all information of the environment must be known in advance, these methods are only suitable for target tracking and obstacle a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/12G05D1/10
CPCG05D1/104G05D1/12
Inventor 丁勇杨勇黄鑫城
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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