A 3D path planning approach for quadrotor UAV navigation

Author(s):  
Wei Li ◽  
Wenwen Chen ◽  
Chong Wang ◽  
Ming Liu ◽  
Yunjian Ge ◽  
...  
2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Karima Benzaid ◽  
Romain Marie ◽  
Noura Mansouri ◽  
Ouiddad Labbani-Igbida

This paper introduces an original 3D path planning approach for Unmanned Aerial Vehicle (UAV) applications. More specifically, the core idea is to generate a smooth and collision-free path with respect to the vehicle dimension. Given a 3D grid representation of the environment, the Generalized Voronoi Graph (GVG) is first approximated using a filtered medial surface (FMS) algorithm on the corresponding navigable space. Based on an efficient pruning criterion, the produced FMS excludes GVG portions corresponding to narrow passages unfitting safe UAV navigation constraints, and thus it defines a set of guaranteed safe trajectories within the environment. Given a set of starting and destination coordinates, an adapted A-star algorithm is then applied to compute the shortest path on the FMS. Finally, an optimization process ensures the smoothness of the final path by fitting a set of 3D Bézier curves to the initial path. For a comparative study, the A-star algorithm is applied directly on the input environment representation and relevant comparative criteria are defined to assert the proposed approach using simulation results.


2021 ◽  
Vol 13 (8) ◽  
pp. 1525
Author(s):  
Gang Tang ◽  
Congqiang Tang ◽  
Hao Zhou ◽  
Christophe Claramunt ◽  
Shaoyang Men

Most Coverage Path Planning (CPP) strategies based on the minimum width of a concave polygonal area are very likely to generate non-optimal paths with many turns. This paper introduces a CPP method based on a Region Optimal Decomposition (ROD) that overcomes this limitation when applied to the path planning of an Unmanned Aerial Vehicle (UAV) in a port environment. The principle of the approach is to first apply a ROD to a Google Earth image of a port and combining the resulting sub-regions by an improved Depth-First-Search (DFS) algorithm. Finally, a genetic algorithm determines the traversal order of all sub-regions. The simulation experiments show that the combination of ROD and improved DFS algorithm can reduce the number of turns by 4.34%, increase the coverage rate by more than 10%, and shorten the non-working distance by about 29.91%. Overall, the whole approach provides a sound solution for the CPP and operations of UAVs in port environments.


Author(s):  
Cosmin Copot ◽  
Marco Marchesi ◽  
Antonio Visioli

Author(s):  
Tianze Zhang ◽  
Xin Huo ◽  
Songlin Chen ◽  
Baoqing Yang ◽  
Guojiang Zhang

Author(s):  
Xiaoxiao Zhuang ◽  
Guangsheng Feng ◽  
Haibin Lv ◽  
Hongwu Lv ◽  
Huiqiang Wang ◽  
...  

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