| In recent years,with the rapid development of cutting-edge technologies such as Unmanned Aerial Vehicle(UAV)technology,communication technology,and artificial intelligence technology,UAV path planning technology has played a significant role in battlefield,rescue,aviation surveying,agricultural plant protection,and other aspects.As an emerging communication method,wireless ultraviolet(UV)communication technology has become an ideal choice for information exchange and flight guidance of drones in complex environments such as strong electromagnetic interference due to its excellent anti-interference ability,non direct vision communication,low eavesdropping rate,and all-weather operation,providing reliable auxiliary support for drone ground communication.Therefore,this article applies wireless ultraviolet communication guidance technology to the field of unmanned aerial vehicle path planning,focusing on the two-dimensional and three-dimensional path planning of unmanned aerial vehicles and the avoidance of external obstacles.The main research content is as follows:(1)Aiming at the path planning problem of UAV in the area with more threats,a path planning method of UAV based on improved bee colony algorithm with chaotic distribution is proposed.Firstly,the flight environment of UAV is modeled,by utilizing the ergodicity and initial value sensitivity of chaotic sequences,the Tent chaotic sequence is introduced into the honey source initialization selection and search strategy of traditional artificial bee colony algorithms,and the roulette wheel selection strategy that originally calculated the honey source selection probability is improved to a reverse roulette wheel selection strategy.The improved artificial bee colony algorithm is applied to UAV path planning.The results show that the average fitness value of the improved bee colony algorithm in the two-dimensional simple threat area is 13.3%and 8.2%lower than that of the particle swarm optimization(PSO)algorithm and the Balanced Evolutionary Strategy Bee Colony Algorithm(BABC)algorithm,respectively,Compared with the other two algorithms,the average fitness of the improved algorithm in the two-dimensional complex threat area is reduced by 20.2%and 31.6%respectively;And in the three-dimensional threat area,the turning angle of the drone’s flight path is slower and smoother compared to the other two algorithms,which verifies that the improved bee colony algorithm in this paper has better stability.(2)In response to the problems of low optimization accuracy and weak obstacle avoidance ability of unmanned aerial vehicles in path planning tasks in obstacle interference environments,wireless ultraviolet communication guidance equipment is suitable for all weather non direct vision communication,covert communication,and various special occasions.Establish a wireless ultraviolet light flight path guidance system,propose a dynamic inertia weight based on exponential decreasing strategy,and introduce artificial potential fields of adjacent path points to ensure the smoothness of the drone path while avoiding falling into local optima;Finally,the diversity and authenticity of the flight environment are ensured through the cost of obstacle interference and UV communication.The results show that the improved Bat Algorithm for Exponential Decreasing Strategies(EDS-IBA)proposed in this paper reduces the average path length planned by 10.7%and 16.3%,respectively,compared to the improved Bat Algorithm based on Differential Evolution Algorithm(DEBA)and traditional Bat Algorithm(BA)in a twodimensional environment,Compared with the other two algorithms,the average path planned in 3D complex space is shortened by 13.7%and 36.2%,and the fitness value of the improved algorithm in this paper is also small when the algorithm reaches the convergence state.Therefore,the improved algorithm in this article is superior to the other two algorithms in terms of path planning ability and algorithm performance,and has good feasibility and effectiveness. |
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