Path Planning Of UAV In Urban Environment

UAV path planning is the key technology of task planning system. In this paper, it takes the UAV path planning in urban environment as the application background, combined with the UAV mission requirements, and then proposed the UAV path planning algorithms which based on Region Segmentation and Lagrange relaxation. Meanwhile, it also works on the problems of time constraints and the minimum area of buildings block. The main aspects of work are as follows:Firstly, it is achieved a buildings Block model of path planning for UAV based on urban environment when given the starting point and the destination point. The algorithm replaces the buildings in urban environment with cylinders, so it's able to calculate the relative block area of buildings to the UAV, in addition, the total block area isn't the sum of each shading area, instead it's a union set, the algorithm calculate the union set by using a program.Secondly, considering in practical application, the UAV Flight mission often requires time and block limitation, Region Segmentation and Lagrange relaxation are introduced in this thesis. In solving the problem of a continuous block, a nonlinear optimization method based on equant search region is proposed. After calculating the curved surface of UAV's flight plane, a path of the minimum area of buildings block is determined by using curve integral, thus approaching the optimal UAV path; in solving the problem of discrete block, the flight area is divided via grid method to form a network diagram which connects the starting point and destination points. In the network graph, each node is defined as a viable node of UAV path. The best feasible point is determined through Lagrange relaxation algorithm so that a optimized path is formed.Finally, the simulations of these two algorithms are implemented, the experimental results shows that the planning algorithms of this paper are accurate and reliable, it is clear that the algorithms improve the convergence speed and overall performance greatly and solve the problem of UAV path planning effectively.