scholarly journals Multi UAV Coverage Path Planning in Urban Environments

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7365
Author(s):  
Javier Muñoz ◽  
Blanca López ◽  
Fernando Quevedo ◽  
Concepción A. Monje ◽  
Santiago Garrido ◽  
...  
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Urban Environments ◽  
Fast Marching ◽  
Flight Pattern ◽  
Cluttered Environments ◽  
Coverage Path Planning ◽  
Area Of Interest ◽  
Smooth Path ◽  
Multi Uav

Coverage path planning (CPP) is a field of study which objective is to find a path that covers every point of a certain area of interest. Recently, the use of Unmanned Aerial Vehicles (UAVs) has become more proficient in various applications such as surveillance, terrain coverage, mapping, natural disaster tracking, transport, and others. The aim of this paper is to design efficient coverage path planning collision-avoidance capable algorithms for single or multi UAV systems in cluttered urban environments. Two algorithms are developed and explored: one of them plans paths to cover a target zone delimited by a given perimeter with predefined coverage height and bandwidth, using a boustrophedon flight pattern, while the other proposed algorithm follows a set of predefined viewpoints , calculating a smooth path that ensures that the UAVs pass over the objectives. Both algorithms have been developed for a scalable number of UAVs, which fly in a triangular deformable leader-follower formation with the leader at its front. In the case of an even number of UAVs, there is no leader at the front of the formation and a virtual leader is used to plan the paths of the followers. The presented algorithms also have collision avoidance capabilities, powered by the Fast Marching Square algorithm. These algorithms are tested in various simulated urban and cluttered environments, and they prove capable of providing safe and smooth paths for the UAV formation in urban environments.

scholarly journals Complete Coverage Path Planning for a Multi-UAV Response System in Post-Earthquake Assessment

Robotics ◽  
2016 ◽  
Vol 5 (4) ◽  
pp. 26 ◽  
Author(s):  
Arman Nedjati ◽  
Gokhan Izbirak ◽  
Bela Vizvari ◽  
Jamal Arkat
Keyword(s):  
Path Planning ◽  
Complete Coverage ◽  
Coverage Path Planning ◽  
Response System ◽  
Earthquake Assessment ◽  
Multi Uav

scholarly journals Complete Coverage Path Planning of an Unmanned Surface Vehicle Based on a Complete Coverage Neural Network Algorithm

2021 ◽  
Vol 9 (11) ◽  
pp. 1163
Author(s):  
Peng-Fei Xu ◽  
Yan-Xu Ding ◽  
Jia-Cheng Luo
Keyword(s):  
Neural Network ◽  
Path Planning ◽  
Target Area ◽  
Complete Coverage ◽  
A Algorithm ◽  
Unmanned Surface Vehicle ◽  
Calculation Time ◽  
Coverage Path Planning ◽  
Practical Applications ◽  
Area Of Interest

In practical applications, an unmanned surface vehicle (USV) generally employs a task of complete coverage path planning for exploration in a target area of interest. The biological inspired neural network (BINN) algorithm has been extensively employed in path planning of mobile robots, recently. In this paper, a complete coverage neural network (CCNN) algorithm for the path planning of a USV is proposed for the first time. By simplifying the calculation process of the neural activity, the CCNN algorithm can significantly reduce calculation time. To improve coverage efficiency and make the path more regular, the optimal next position decision formula combined with the covering direction term is established. The CCNN algorithm has increased moving directions of the path in grid maps, which in turn has further reduced turning-angles and makes the path smoother. Besides, an improved A* algorithm that can effectively decrease path turns is presented to escape the deadlock. Simulations are carried out in different environments in this work. The results show that the coverage path generated by the CCNN algorithm has less turning-angle accumulation, deadlocks, and calculation time. In addition, the CCNN algorithm is capable to maintain the covering direction and adapt to complex environments, while effectively escapes deadlocks. It is applicable for USVs to perform multiple engineering missions.

Asynchronous Reliability-Aware Multi-UAV Coverage Path Planning

2021 ◽  
Author(s):  
Mickey Li ◽  
Arthur Richards ◽  
Mahesh Sooriyabandara
Keyword(s):  
Path Planning ◽  
Coverage Path Planning ◽  
Multi Uav

scholarly journals Convex Decomposition for a Coverage Path Planning for Autonomous Vehicles: Interior Extension of Edges

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4165 ◽  
Author(s):  
Lasse Damtoft Nielsen ◽  
Inkyung Sung ◽  
Peter Nielsen
Keyword(s):  
Path Planning ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Decomposition Methods ◽  
Target Area ◽  
Solution Approach ◽  
Coverage Path Planning ◽  
Convex Decomposition ◽  
Common Solution ◽  
Area Of Interest

To cover an area of interest by an autonomous vehicle, such as an Unmanned Aerial Vehicle (UAV), planning a coverage path which guides the unit to cover the area is an essential process. However, coverage path planning is often problematic, especially when the boundary of the area is complicated and the area contains several obstacles. A common solution for this situation is to decompose the area into disjoint convex sub-polygons and to obtain coverage paths for each sub-polygon using a simple back-and-forth pattern. Aligned with the solution approach, we propose a new convex decomposition method which is simple and applicable to any shape of target area. The proposed method is designed based on the idea that, given an area of interest represented as a polygon, a convex decomposition of the polygon mainly occurs at the points where an interior angle between two edges of the polygon is greater than 180 degrees. The performance of the proposed method is demonstrated by comparison with existing convex decomposition methods using illustrative examples.

scholarly journals Survey on Coverage Path Planning with Unmanned Aerial Vehicles

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 4 ◽  
Author(s):  
Tauã Cabreira ◽  
Lisane Brisolara ◽  
Paulo R. Ferreira Jr.
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Performance Metrics ◽  
Partial Information ◽  
Convex Polygons ◽  
Cellular Decomposition ◽  
Coverage Path Planning ◽  
Area Of Interest ◽  
Aerial Vehicles ◽  
Smart Farming

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.

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