Route Planning Of Forest UAV Based On Interval Differential Evolution Algorithm

Forest is the largest terrestrial ecosystem on earth,is an important link in the global biosphere,is the human survival and development of resources and environment.Forest resources have great significance to our country.Forest fire is the most destructive in forest disasters and the most terrible disaster in forestry.Traditional forest fire monitoring methods include ground monitoring,manual inspection,aerospace remote sensing technology,satellite monitoring technology,etc.,but these traditional forest fire prevention and control methods have certain shortcomings and deficiencies.Uav has the characteristics of low cost,fast maneuvering speed,simple maintenance and so on.Using UAV for forest fire prevention and control has become a technical means.When UAV flies in the unknown space of forest environment,it will face a large number of dynamic and unknown limiting factors,and the change of these factors will lead to the uncertainty of structural parameters in the modeling process.The uncertainty factor of UAV in forest flight path planning will have a great influence on the actual optimal flight path.Aiming at the optimal cruise route of UAV in forest area,this paper designs the obstacle avoidance link in two-dimensional plane and three-dimensional space of UAV,and combines the real-time flame detection algorithm of UAV based on the theoretical framework of YOLOv5 to discover fire situation and prevent fire in time.The uncertain factors such as obstacle radius,flight conditions,climbing and descending,maneuvering performance and forest parameter selection were quantified by the non-probabilistic method,and the uncertain flight path planning model of UAV was established.By describing the uncertain parameters and forest parameter selection,the interval differential evolution algorithm was used to solve the flight path optimization of forest UAV.In the framework of interval differential evolution algorithm,the interval probability model is used to evaluate the interval constraints of uncertain optimization problems,and the interval priority rule is used to select the current optimal solution to be retained in the next evolutionary population,so as to improve the accuracy of the algorithm.Research showed that:(1)After the introduction of uncertainty factors,the optimal path of UAV changes from a certain value to an interval number,and the path of UAV cruise is any value in the interval.The decision maker should select the appropriate optimal path according to the specific terrain of the forest area and provide the appropriate power source for UAV.(2)The forest UAV flight path optimization model based on the interval differential evolution algorithm can directly deal with the interval uncertainty existing in the objective function and constraints without transformation,and has high applicability and fidelity of results.It can effectively consider the influence of uncertain parameters on the optimal path,and has high optimization efficiency.(3)Compared with the transformation method of interval uncertainty optimization,the interval differential evolution algorithm,namely the direct method of interval uncertainty optimization,generates a smaller path length,and although the number of calls is much larger than the transformation method,its search results are more stable and robust,and its global path planning ability under uncertainty space shows good advantages.