Research On UAV Track Planning With Improved Bacterial Foraging Optimization Algorithm

Nowadays,the application of unmanned aerial vehicle(UAV)has become a growth industry,for example,under the outbreak of COVID-19,a large number of community became "isolated islands" because of closed-end management.This moment,the UAV can achieve non-contact distribution function to obtain prominent advantage,including completing safe and fast delivery,avoiding the waste of manpower and other resources and preventing cross infection.Under the condition of insufficient resources,inconvenient transportation and strong time dependence,the UAV can centrally deliver emergency medical supplies such as organs and blood samples within a certain range,which can guarantee large-scale emergency medical activities to a large extent.In addition,the UAV can also be used in fire inspection,disaster relief,military reconnaissance,etc.More and more various kinds of actual application scenario requires a better UAV flight path planning ability,while the existing route planning algorithm and the technology is still not fully meet the requirements of the task,so path planning algorithm needs optimized in further research.For existing limitations of UAV flight path planning methods including the slow convergence speed,the low efficiency and so on,in this paper,we study and provide the path planning structure based on the improved bacteria foraging optimization algorithm to solve existing problems.We improved the bacteria foraging optimization algorithm from three aspects : first of all,changing the unit of fixed step length into the adaptive step length;secondly,embedding the learning factor idea of particle swarm optimization(PSO)when bacteria swim;thirdly,changing the fixed migration probability to the adaptive migration probability.The improved bacterial foraging algorithm is also demonstrated by four testing functions.At the same time,the objective function of flight cost is proposed to find the optimal solution of the problem to carry out the UAV flight path planning,and the three-dimensional environment is established by using the digital elevation data.In this paper,the feasibility and optimization of the algorithm are verified by the simulation of small UAV flying by ground obstacle and the simulation of large UAV flying over low altitude obstacle.The results show that the track planning structure based on improved bacterial foraging optimization algorithm has the characteristics of shorter track length,smoother and faster convergence speed,and can be widely used in many types of UAV track planning.On the basis of existing track planning techniques and algorithms,the improved bacterial foraging algorithm is applied to UAV track planning so that it can be well applied to flight scenarios with multiple threat areas and complex terrain and provides a new way for track planning.