Survey on Coverage Path Planning with Unmanned Aerial Vehicles

Cabreira, Tauã M.; Brisolara, Lisane; Ferreira, Paulo R.

doi:10.3390/drones3010004

Cited by 423 publications

(268 citation statements)

References 89 publications

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“…We can also cite Reference [12], which proposed a comparative study of existing UAV path-planning algorithms with both heuristic and non-heuristic methodologies including Potential Field, Genetic, Floyd-Warshall, Mixed Integer Linear Programming (MILP) and so forth. The review in Reference [13] was interested in Coverage Path Planning problems (CPP) with UAV. The authors surveyed existing studies addressing simple geometric flight patterns for the CPP problem.…”

Section: Overview Of the Trajectory Computation Problems And Existingmentioning

confidence: 99%

“…For other problems than routing, for instance for problems of drone control, collision avoidance and, in general, problems of drone mobility at small time scales, there already exist reviews, such as the ones addressing path planning [11,13,14], presented in the previous section and a large literature on drone control.…”

Section: Motivation and Organization Of This Reviewmentioning

confidence: 99%

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A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles

Khoufi

Laouiti

Adjih

2019

Drones

124

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The use of Unmanned Aerial Vehicles (UAVs) is rapidly growing in popularity. Initially introduced for military purposes, over the past few years, UAVs and related technologies have successfully transitioned to a whole new range of civilian applications such as delivery, logistics, surveillance, entertainment, and so forth. They have opened new possibilities such as allowing operation in otherwise difficult or hazardous areas, for instance. For all applications, one foremost concern is the selection of the paths and trajectories of UAVs, and at the same time, UAVs control comes with many challenges, as they have limited energy, limited load capacity and are vulnerable to difficult weather conditions. Generally, efficiently operating a drone can be mathematically formalized as a path optimization problem under some constraints. This shares some commonalities with similar problems that have been extensively studied in the context of urban vehicles and it is only natural that the recent literature has extended the latter to fit aerial vehicle constraints. The knowledge of such problems, their formulation, the resolution methods proposed—through the variants induced specifically by UAVs features—are of interest for practitioners for any UAV application. Hence, in this study, we propose a review of existing literature devoted to such UAV path optimization problems, focusing specifically on the sub-class of problems that consider the mobility on a macroscopic scale. These are related to the two existing general classic ones—the Traveling Salesman Problem and the Vehicle Routing Problem. We analyze the recent literature that adapted the problems to the UAV context, provide an extensive classification and taxonomy of their problems and their formulation and also give a synthetic overview of the resolution techniques, performance metrics and obtained numerical results.

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Section: Overview Of the Trajectory Computation Problems And Existingmentioning

confidence: 99%

Section: Motivation and Organization Of This Reviewmentioning

confidence: 99%

A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles

Khoufi

Laouiti

Adjih

2019

Drones

124

View full text Add to dashboard Cite

show abstract

“…Recent approaches in 3D path planning concentrate more on detecting and avoiding obstacle in a 3D view [13][14][15][16][17][18][19]. They have not given priority to compromise between the energy efficiency and the completeness of the area coverage [20] in the presence of obstacles. In our work, we propose an energy aware 3D obstacle avoidance (EAOA) which plans a full coverage path for an area of interest with the ability to avoid obstacles in a 3D view using a grid-based technique.…”

Section: Introductionmentioning

confidence: 99%

EAOA: Energy-Aware Grid-Based 3D-Obstacle Avoidance in Coverage Path Planning for UAVs

Ghaddar

Merei

2020

Future Internet

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The presence of obstacles like a tree, buildings, or birds along the path of a drone has the ability to endanger and harm the UAV’s flight mission. Avoiding obstacles is one of the critical challenging keys to successfully achieve a UAV’s mission. The path planning needs to be adapted to make intelligent and accurate avoidance online and in time. In this paper, we propose an energy-aware grid based solution for obstacle avoidance (EAOA). Our work is based on two phases: in the first one, a trajectory path is generated offline using the area top-view. The second phase depends on the path obtained in the first phase. A camera captures a frontal view of the scene that contains the obstacle, then the algorithm determines the new position where the drone has to move to, in order to bypass the obstacle. In this paper, the obstacles are static. The results show a gain in energy and completion time using 3D scene information compared to 2D scene information.

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“…Most of the existing surveys in this topic address issues such as perception, exploration, guidance and control. A few surveys address the CPP problem focusing on single robot CPP problems and briefly mentioning the multirobot as an extension [26,79], or focusing on multi-robot area coverage problems [77]. Although some of the techniques performed in single robot CPP can be extended and applied to multi-robot systems, several additional aspects must be considered including viewpoints generation, communication/task allocation, robustness (failure handling), and mapping.…”

Section: Introductionmentioning

confidence: 99%

A survey on multi-robot coverage path planning for model reconstruction and mapping

Taha²,

et al. 2019

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There has been an increasing interest in researching, developing and deploying multi-robot systems. This has been driven mainly by: the maturity of the practical deployment of a single-robot system and its ability to solve some of the most challenging tasks. Coverage path planning (CPP) is one of the active research topics that could benefit greatly from multi-robot systems. In this paper, we surveyed the research topics related to multi-robot CPP for the purpose of mapping and model reconstructions. We classified the topics into: viewpoints generation approaches; coverage planning strategies; coordination and decision-making processes; communication mechanism and mapping approaches. This paper provides a detailed analysis and comparison of the recent research work in this area, and concludes with a critical analysis of the field, and future research perspectives.

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Survey on Coverage Path Planning with Unmanned Aerial Vehicles

Cited by 423 publications

References 89 publications

A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles

A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles

EAOA: Energy-Aware Grid-Based 3D-Obstacle Avoidance in Coverage Path Planning for UAVs

A survey on multi-robot coverage path planning for model reconstruction and mapping

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