Research On Unmanned Aerial Vehicle Path Intelligent Planning Algorithm

With the rapid development of the network and the continuous maturity of artificial intelligence technology,many intelligent robots have emerged in life,the UAV(Unmanned aerial vehicle)is one of them.UAV is the unmanned aircraft operated by radio remote control devices and self-contained program,it is operated entirely or intermittently by on-board computers.Compared to the manned aircraft,it has many advantages,such as small size,low cost,easy to use and portable camera or other sensors.UAVs are used in various tasks in industries such as commerce,agriculture,and military applications,including environmental monitoring,target identification,border patrols,and search and rescue assistance.However,UAVs also exposed a lot of problems,the most important issue is the endurance of UAVs.Due to the limited payload of UAVs,it is not possible to add more batteries to the UAVs.Only when the UAVs perform their tasks,can they fly as effective paths as possible.So path planning is the primary issue we want to solve when we study UAVs.There are already many UAV path planning solutions.However,these solutions are limited to offline environments,and there are few UAV path planning techniques in dynamic environments.And the existing scheme uses the distance traveled by the UAV as a cost function to judge the effectiveness of a route.In fact,the UAV path should be evaluated by the energy consumption of the UAV.Aiming at the above two points,this paper designs a UAV path planning scheme based on evolutionary algorithm and a dynamic environment UAV path planning scheme based on artificial potential field.The main research contents of this paper are as follows:(1)This paper proposes a UAV path planning scheme based on evolutionary algorithm.In this scheme,we propose three cost function path security cost,length cost and smoothness cost.The path security cost is used to determine whether the path is feasible;the length cost and smoothness cost of the path directly affect the cost of the energy consumption of the UAV flight.We proposed a heuristic evolutionary algorithm that designed several evolutionary operations: substitution operations,crossover operations,mutation operations,length operations,and smoothness operations.Through these operations to enhance our build path effect.Under the analysis of experimental results,we proved that our solution is feasible.(2)This paper proposes a dynamic environment UAV path planning scheme based on artificial potential field method.In this solution,the drone can safely and effectively fly safely in a dynamic environment.Firstly,a modeling scheme of dynamic obstacles is proposed,which analyzes the collision position of dynamic obstacles with UAVs,statically dynamic obstacles,and establishes a new environmental model.Secondly,in order to meet the dynamic environment of UAVs.In the real-time planning path requirements,a UAV path planning scheme based on artificial potential field method is proposed.The scheme analyzes the shortcomings of the existing artificial potential field method,and then proposes several improvement schemes,and finally real-time planning.The flight path of the UAV.Finally,the feasibility of our scheme was verified by simulation experiments.