Unmanned aerial vehicle optimal path searching method based on improved fluid disturbance and sparrow algorithm

Abstract

The invention relates to an unmanned aerial vehicle optimal path searching method based on improved fluid disturbance and a sparrow algorithm. The method comprises the steps: firstly, generating a plurality of planning routes through employing different obstacle reaction coefficients according to an improved fluid disturbance algorithm; then, searching a reaction coefficient of an optimal obstacle by calculating fitness through a sparrow search algorithm; and finally, generating an optimal search path by using the current optimal obstacle reaction coefficient through an improved fluid perturbation algorithm. Compared with a traditional fluid perturbation algorithm, the problem of local extreme points is solved, the accuracy is higher, and the optimal obstacle reaction coefficient is automatically searched by using a sparrow search algorithm; compared with other types of unmanned aerial vehicle optimal path searching methods, the method has the advantages that the searching speed is increased under the condition that the accuracy is ensured, so that quick response can be performed when an accident at an emergency traffic intersection is dealt with; and on the premise of ensuring safe and rapid flight of the unmanned aerial vehicle in obstacle avoidance, the accuracy of planning the optimal trajectory and the smoothness of the trajectory can also be ensured.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicles and relates to an optimal path search method for unmanned aerial vehicles based on improved fluid disturbance and sparrow algorithm. Background technique [0002] UAV (Unmanned Aerial Vehicle, referred to as UAV), refers to a power-driven unlimited remote control or autonomous flight, unmanned and reusable aircraft. In recent years, due to the portability of small civilian drones, Features such as maneuverability, vertical take-off and landing, and automatic control of flight have been developed rapidly in both military and civilian fields. In the military field, multi-rotor UAVs can be used as reconnaissance aircraft to obtain ground intelligence, support ground personnel operations, and can also conduct bombing operations in clusters. In the civil field, the most functions are aerial photography, ground surveying and mapping, personnel search and rescue, power inspection, traff...

AI Technical Summary

Problems solved by technology

It is difficult to choose an appropriate learning rate. If the setting is too large, the learning curve will fluctuate violently, and the value of the cost function will usually increase significantly; if it is too small, the learning process will be very slow. If the initial learning rate is too low, the learning may be stuck at a fairly high cost

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