Multiple-unmanned aerial vehicle collaborative area searching method under communication constrains

Abstract

The invention provides a multiple-unmanned aerial vehicle collaborative area searching method under the communication constrains. The method comprises the following steps of: firstly setting an initial position of multiple unmanned aerial vehicles, parameters of the communication constrain condition and search finishing time, selecting a point with the minimum cost as a next way-point position of all unmanned aerial vehicles, and judging whether the way point meets the boundary constraint condition; when one unmanned aerial vehicle flies to the way point meeting the boundary constraint condition, judging whether other unmanned aerial vehicles are in the communication distance range of the unmanned aerial vehicle, and exchanging probability graph data with the unmanned aerial vehicle with closest distance; and finally, calculating the area coverage rate and judging whether the search finishing time is reached. The multiple-unmanned aerial vehicle collaborative area searching method has the advantages that the influence of the communication constrain on the multiple-unmanned aerial vehicle cooperative system can be eliminated or weakened, the multiple unmanned aerial vehicles can finish the search task at minimum cost and the coverage rate of the search area is increased.

Description

technical field [0001] The invention relates to a method for multiple unmanned aerial vehicles to take off from different locations and search an unknown area under communication constraints, and related fields include cooperative control and communication technology. Background technique [0002] Multi-UAV collaborative area search is one of the important contents of multi-UAV cooperative missions. It can be applied to personnel search and positioning in disasters, as well as accident site survey and detection. The research at home and abroad is very extensive. "Maximizing Search Coverage Using Future Path Proiection for Cooperative Multiple UAVs with Limited Communication Ranges" proposed by Pedro DeLima and Daniel Pack uses FPP (Future Path Projection, future path planning) algorithm enables multi-UAV collaborative search under the limitation of communication distance to achieve the maximum search coverage. The algorithm firstly gives the search cost function for the UAV...

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Problems solved by technology

[0003] The search cost function proposed by this algorithm has some vague concepts, no quantification, and poor operability; this algorithm only considers the influence of communication distance limitation on multi-UAV cooperative search, and does not consider other communication constraints. Such as the limitation of communication bandwidth, the research on communication constraints is not deep enough

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