Complete coverage path planning for aerial vehicle flocks deployed in outdoor environments

Guastella, Dario Calogero; Cantelli, Luciano; Giammello, Giuseppe; Melita, Carmelo Donato; Spatino, Gianluca; Muscato, Giovanni

doi:10.1016/j.compeleceng.2019.02.024

Cited by 36 publications

(14 citation statements)

References 14 publications

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“…e driving speed of a vehicle on a certain route during a certain period of time is determined by the average value of the road traffic index on the route during this period of time. And the speed of the vehicle does not change in each time period, regardless of the speed change process across the time period [21]. 100. e larger the value, the more congested the road [22].…”

Section: Model Buildingmentioning

confidence: 99%

Path Optimization Model for Urban Transportation Networks under the Perspective of Environmental Pollution Protection

Liu

2021

Journal of Advanced Transportation

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In view of the lack of consideration of environmental protection performance in the traditional path optimization model, a path optimization model for urban traffic networks from the perspective of environmental pollution protection is proposed. Firstly, the urban real-time traffic condition is expressed by the road traffic state index, and an integer programming model is established to optimize the route with the goal of low carbon and shortest distribution time. Then, a hybrid particle swarm optimization algorithm combined with adaptive disturbance mechanism based on variable neighborhood descent is designed, which can better carry out adaptive disturbance according to the situation that the population falls into local extreme value, and the 2-opt local search method is introduced to improve the quality of solution. Finally, the improved particle swarm optimization algorithm is used to solve the two-objective model to obtain the Pareto front solution set, that is, the path scheme under real-time traffic conditions. The experimental demonstration of the proposed model based on two application scenarios shows that its distribution cost, distribution time, and carbon emission are 1975 yuan, 27 h, and 213 kg, respectively, which are better than other comparison models and have high application value.

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Section: Model Buildingmentioning

confidence: 99%

Path Optimization Model for Urban Transportation Networks under the Perspective of Environmental Pollution Protection

Liu

2021

Journal of Advanced Transportation

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“…When there is only one UAV, the condition (8) is not guaranteed to hold. In this case, an interesting issue is how many targets in Q can one UAV survey subject to condition (8). Such a number depends on how the targets spread in Q.…”

Section: While 1 Domentioning

confidence: 99%

“…Considering the inefficiency of using a single large UAV, especially in large areas, it is a trend to employ multiple small UAVs to complete missions quickly [6]. For example, for the periodical area sensing mission, much time can be saved by well designing complete coverage paths for a team of UAVs that operate in a parallel manner [7,8]. Another situation is to monitor some fast changing environment such as bushfires [9], and deploying a UAV team can generally collect more temporal-spatial data than using a single UAV.…”

Section: Introductionmentioning

confidence: 99%

Reactive Autonomous Navigation of UAVs for Dynamic Sensing Coverage of Mobile Ground Targets

Huang

Savkin

2020

Sensors

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This paper addresses a problem of autonomous navigation of unmanned aerial vehicles (UAVs) for the surveillance of multiple moving ground targets. The ground can be flat or uneven. A reactive real-time sliding mode control algorithm is proposed that navigates a team of communicating UAVs, equipped with ground-facing video cameras, towards moving targets to increase some measure of sensing coverage of the targets by the UAVs. Moreover, the Voronoi partitioning technique is adopted to reduce the movement range of the UAVs and decrease the revisit times of the targets. Extensive computer simulations, from the simple case with one UAV and multiple targets to the complex case with multiple UAVs and multiple targets, are conducted to demonstrate the performance of the developed autonomous navigation algorithm. The scenarios where the terrain is uneven are also considered. As shown in the simulation results, although the additional VP technique leads to some extra computation burden, the usage of the VP technique considerably reduces the target revisit time compared to the algorithm without this technique.

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“…According to the construction requirements in site leveling, the process required is to completely cover the field to find a path that covers the remaining working space to ensure the maximum coverage and minimum repetition rate (Wang & Bo, 2014). Most of the existing complete coverage path planning (CCPP) research are about airplanes, cleaning robots, and agricultural vehicles (Dakulović et al, 2011; Guastella & Cantelli, 2019; Lakshmanan & Mohan, 2020; Nilsson et al, 2020; Kun, 2020; Sandamurthy & Ramanujam, 2019; Taghavifar & Rakheja, 2021), there are few studies on earth‐moving engineering machinery. This article effectively solves the CCPP problem considering the bulldozer's construction rules.…”

Section: Introductionmentioning

confidence: 99%

Complete coverage path planning and performance factor analysis for autonomous bulldozer

Zhou

Dou

et al. 2022

Journal of Field Robotics

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With the development of intelligent machinery, path planning of autonomous bulldozers plays an important role to solve the problems of efficiency in future construction sites. How to plan the path that meets the construction requirements is the key problem. This study investigates the standardized construction workmanship and moving rules of the bulldozer to add rules and path selection strategies to the algorithm. This study establishes the path planning model of bulldozer's leveling, considering the limitations of the traditional bioinspired neural network algorithm, an improved complete coverage path planning method is proposed. An integrated framework is proposed for an automatic bulldozer with a sensor system for a field experiment to verify the feasibility of the method. According to the comparative statistical simulation results, the effectiveness of the method is verified, and the effects of different factors on the path planning results are analyzed.

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Complete coverage path planning for aerial vehicle flocks deployed in outdoor environments

Cited by 36 publications

References 14 publications

Path Optimization Model for Urban Transportation Networks under the Perspective of Environmental Pollution Protection

Path Optimization Model for Urban Transportation Networks under the Perspective of Environmental Pollution Protection

Reactive Autonomous Navigation of UAVs for Dynamic Sensing Coverage of Mobile Ground Targets

Complete coverage path planning and performance factor analysis for autonomous bulldozer

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