A Study on the Path Planning Algorithm of the Unmanned Aerial Vehicle

2020 ◽  
Author(s):  
Deyu Zhang ◽  
Yue Gu ◽  
Yanhui Lv ◽  
Haolei Sun
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicle ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Path Planning Algorithm

scholarly journals A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

2019 ◽  
Vol 9 (7) ◽  
pp. 1470 ◽  
Author(s):  
Abdul Majeed ◽  
Sungchang Lee
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicle ◽  
Travelling Salesman Problem ◽  
Urban Environments ◽  
Flight Path ◽  
Computational Time ◽  
Minimum Length ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Path Planning Algorithm

This paper presents a new coverage flight path planning algorithm that finds collision-free, minimum length and flyable paths for unmanned aerial vehicle (UAV) navigation in three-dimensional (3D) urban environments with fixed obstacles for coverage missions. The proposed algorithm significantly reduces computational time, number of turns, and path overlapping while finding a path that passes over all reachable points of an area or volume of interest by using sensor footprints’ sweeps fitting and a sparse waypoint graph in the pathfinding process. We devise a novel footprints’ sweep fitting method considering UAV sensor footprint as coverage unit in the free spaces to achieve maximal coverage with fewer and longer footprints’ sweeps. After footprints’ sweeps fitting, the proposed algorithm determines the visiting sequence of footprints’ sweeps by formulating it as travelling salesman problem (TSP), and ant colony optimization (ACO) algorithm is employed to solve the TSP. Furthermore, we generate a sparse waypoint graph by connecting footprints’ sweeps’ endpoints to obtain a complete coverage flight path. The simulation results obtained from various scenarios fortify the effectiveness of the proposed algorithm and verify the aforementioned claims.

Study on UAV Path Planning Oriented to Optimization of Positioning Error

2013 ◽  
Vol 791-793 ◽  
pp. 1357-1361
Author(s):  
Cheng Dong Wu ◽  
Jian Yu Yang ◽  
Yao Sun ◽  
Yun Zhou Zhang
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Network ◽  
Path Planning ◽  
Unmanned Aerial Vehicle ◽  
Wireless Sensor ◽  
Positioning Error ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Geometric Dilution Of Precision ◽  
Path Planning Algorithm

For many applications in wireless sensor network (WSN) node positioning by unmanned aerial vehicle (UAV) need a path planning algorithm optimizing positioning error. In this article, we present an algorithm combining Voronoi diagram and geometric dilution of precision (GDOP) to make track points, considering both the efficiency of flying and accuracy of positioning. Then, we connect all the track points using genetic algorithm and we get the minimized flight path.

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