Research On Path Planning Of Quadrotor Unmanned Aerial Vehicle In Complex Environment

In recent years,with the progress of science and technology,Unmanned Aerial Vehicle(UAV)technology has developed rapidly.As the most widely used aircraft,the quadrotor UAV has the advantages of simple structure,flexible control and strong carrying capacity,which can replace the special work of human in complex and dangerous environment.Path planning is the basis of UAV autonomous flight,and path planning algorithm is the core of path planning.At present,many traditional path planning algorithms are difficult to achieve expected results in complex environments.Therefore,this paper takes path planning of quadrotor UAV as the research object,and makes further research and improvement on obstacle avoidance of planning algorithms in complex environments.The main research contents are as follows:(1)The basic theory and related technology of path planning are summarized.Firstly,geometric figure method and grid method are proposed to simplify the process of environment modeling for 2D and 3D path planning.Secondly,according to the physical performance limitations of the quadrotor UAV,the constraint conditions and cost functions of the path planning are analyzed.Finally,Bezier curve and B-spline curve method are proposed for smoothing and flyability of flight path.(2)The path planning algorithm in high density environment is studied.Aiming at the shortcomings of Rapidly-Exploring Random Tree(RRT)blind searching,slow convergence speed and unsuitable initial flight path for UAV,an improved RRT-Connect algorithm is proposed.Firstly,two random trees are set at the start point and the target point to speed up the path search.Secondly,the target point gravity is added to make the random tree extend towards the target point and accelerate the convergence rate of the algorithm.Thirdly,constraints are added to the node to make the path meet the UAV dynamics constraints.Finally,B-spline curve is used to smooth the path of the quadrotor UAV.Through simulation experiments,it is verified that the improved algorithm can not only quickly search feasible path in the two-dimensional dense environment,but also effectively get the path solution in the three-dimensional complex environment.(3)The path planning algorithm in local dynamic obstacle environment is studied.To solve the problem of unreachable target point by Artificial Potential Field(APF)method,the relative distance information between UAV and target point is introduced into traditional repulsive field function,which solves the problem that UAV cannot reach target point smoothly due to repulsive effect of obstacles near target point.In addition,in view of the deficiency of obstacle avoidance ability of artificial potential field method in dynamic environment,the relative speed information between UAV and target point and between UAV and obstacle is introduced into traditional potential field function,which improves the ability of UAV to avoid moving obstacles in dynamic environment.Finally,the effectiveness of the improved artificial potential field method is verified in MATLAB platform.