Coverage path planning for UAVs based on enhanced exact cellular decomposition method

Mechatronics ◽  
2011 ◽  
Vol 21 (5) ◽  
pp. 876-885 ◽  
Author(s):  
Yan Li ◽  
Hai Chen ◽  
Meng Joo Er ◽  
Xinmin Wang
Robotica ◽  
2020 ◽  
pp. 1-22
Author(s):  
K. R. Guruprasad ◽  
T. D. Ranjitha

SUMMARY A new coverage path planning (CPP) algorithm, namely cell permeability-based coverage (CPC) algorithm, is proposed in this paper. Unlike the most CPP algorithms using approximate cellular decomposition, the proposed algorithm achieves exact coverage with lower coverage overlap compared to that with the existing algorithms. Apart from a formal analysis of the algorithm, the performance of the proposed algorithm is compared with two representative approximate cellular decomposition-based coverage algorithms reported in the literature. Results of demonstrative experiments on a TurtleBot mobile robot within the robot operating system/Gazebo environment and on a Fire Bird V robot are also provided.


2001 ◽  
Author(s):  
Howie Choset ◽  
Ercan U. Acar ◽  
Yangang Zhang ◽  
Mark Schervish

Abstract Coverage path planning is the determination of a path that a robot must take in order to pass itself, a detector, or some other effector over each point in an environment. Applications include demining, floor scrubbing, and inspection. In previous work, we developed the boustrophedon cellular decomposition, an exact cellular decomposition approach, for the purposes of coverage. Each cell in the boustrophedon decomposition is covered with simple back and forth motions. Therefore, coverage is reduced to finding an exhaustive path through a graph that represents the adjacency relationships of the cells in the boustrophedon decomposition. Such a path will ensure that a detector passes over all points in the environment, but it does not guarantee that all ordnance is indeed detected because mine detectors have error. Therefore, we also consider probabilistic methods to determine paths for the robot to maximize the likelihood of detecting all ordnance in a target location using a priori known information.


Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 4 ◽  
Author(s):  
Tauã Cabreira ◽  
Lisane Brisolara ◽  
Paulo R. Ferreira Jr.

Coverage path planning consists of finding the route which covers every point of a certain area of interest. In recent times, Unmanned Aerial Vehicles (UAVs) have been employed in several application domains involving terrain coverage, such as surveillance, smart farming, photogrammetry, disaster management, civil security, and wildfire tracking, among others. This paper aims to explore and analyze the existing studies in the literature related to the different approaches employed in coverage path planning problems, especially those using UAVs. We address simple geometric flight patterns and more complex grid-based solutions considering full and partial information about the area of interest. The surveyed coverage approaches are classified according to a classical taxonomy, such as no decomposition, exact cellular decomposition, and approximate cellular decomposition. This review also contemplates different shapes of the area of interest, such as rectangular, concave and convex polygons. The performance metrics usually applied to evaluate the success of the coverage missions are also presented.


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):  
Aleksandr Ianenko ◽  
Alexander Artamonov ◽  
Georgii Sarapulov ◽  
Alexey Safaraleev ◽  
Sergey Bogomolov ◽  
...  

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