Unmanned aerial vehicle path planning method for minimizing number of unmanned aerial vehicles

Abstract

The invention provides an unmanned aerial vehicle path planning method for minimizing the number of unmanned aerial vehicles, which mainly solves the problem of minimizing the number of unmanned aerial vehicles in the existing unmanned aerial vehicle path planning scheme, and comprises the following implementation steps: 1) initializing parameters; 2) constructing a to-be-accessed sensor set and initializing a local optimal path set; 3) calculating flight energy consumption, hovering energy consumption and communication energy consumption of the unmanned aerial vehicle; 4) planning flight paths for a given number of unmanned aerial vehicles by adopting an improved ant colony algorithm, and determining a local optimal path set; and 5) obtaining an unmanned aerial vehicle path planning result according to the characteristics of the local optimal path set. According to the invention, on the basis of accessing all the sensors, the minimum number of unmanned aerial vehicles are used to complete the task, the system cost is reduced, and the total energy consumption of the unmanned aerial vehicles is reduced.

Description

technical field [0001] The invention belongs to the field of communication technology, and relates to a UAV path planning method, in particular to a UAV path planning method for realizing the minimization of the number of UAVs, which can be used for data collection under the condition that the cost of UAVs is limited. Background technique [0002] In recent years, UAV technology has developed rapidly and plays an important role in military and civilian fields. The lightweight body and flexible movement mode enable the UAV to collect and transmit data in complex environments. In practical applications, whether it is a fuel-based UAV or a rechargeable UAV, the energy is limited, and the economic cost of purchasing a UAV cannot be ignored. The price of a civilian UAV can reach When using multiple drones to access sensor nodes, the more drones used, the greater the total cost of accessing sensor nodes. Therefore, in the UAV network, it is necessary to determine the minimum num...

AI Technical Summary

Problems solved by technology

In this scheme, the node closest to the current sensor node is selected as the next node to be visited by the UAV every time, without considering the distance between the sensor node and the starting position of the UAV, and according to the UAV itself The optimal sensor node access method plans the path, which cannot avoid the impact on other drones, so the number of drones used is not necessarily the minimum

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