A new vibrational genetic algorithm enhanced with a Voronoi diagram for path planning of autonomous UAV

Pehlivanoglu, Y. Volkan

doi:10.1016/j.ast.2011.02.006

Cited by 280 publications

(125 citation statements)

References 14 publications

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“…In solving practical problems, the GA is also used as an efficient algorithm for solving the problem of task assignment and trajectory optimization [5]. In most cases, it exhibits better results [13] and shorter solution times [14] than other algorithms. Therefore, we used the GA to solve the DTOP-VTW-VP in this study.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…When solving the OP with time windows [52] or OP with stochastic profits [47], the GA results have advantages over those from other heuristic algorithms. Meanwhile, in practical application processes such as UAVs task allocation [53] and mission planning [54], the GA not only requires less calculating time [14] but also gives better results [13].…”

Section: Related Workmentioning

confidence: 99%

“…Constraint (13) shows that the spraying time is needed when visiting farmlands. Constraint (14) ensures that each farmland can be visited at most once in all of time windows. Constraint (15) ensures that the time of spraying must be within time window.…”

Section: Task Profitmentioning

confidence: 99%

See 2 more Smart Citations

Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm

Luo

Niu

Zhu

et al. 2017

Mathematical Problems in Engineering

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Task allocation is the key factor in the spraying pesticides process using unmanned aerial vehicles (UAVs), and maximizing the effects of pesticide spraying is the goal of optimizing UAV pesticide spraying. In this study, we first introduce each UAV's kinematic constraint and extend the Euclidean distance between fields to the Dubins path distance. We then analyze the two factors affecting the pesticide spraying effects, which are the type of pesticides and the temperature during the pesticide spraying. The time window of the pesticide spraying is dynamically generated according to the temperature and is introduced to the pesticide spraying efficacy function. Finally, according to the extensions, we propose a team orienteering problem with variable time windows and variable profits model. We propose the genetic algorithm to solve the above model and give the methods of encoding, crossover, and mutation in the algorithm. The experimental results show that this model and its solution method have clear advantages over the common manual allocation strategy and can provide the same results as those of the enumeration method in small-scale scenarios. In addition, the results also show that the algorithm parameter can affect the solution, and we provide the optimal parameters configuration for the algorithm.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm

Luo

Niu

Zhu

et al. 2017

Mathematical Problems in Engineering

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show abstract

“…The use of such approaches does not provide an appropriate optimization solution to the UAV flight planning problem. When using the genetic algorithm [8], the time criterion for solving the problem is not taken into account. In [9], the motion control problem for groups of UAVs and unmanned ground robots as part of a system of unmanned vehicles for performing tasks is considered.…”

Section: Research Of Existing Solutions Of the Problemmentioning

confidence: 99%

Planning the flight routes of the unmanned aerial vehicle by solving the travelling salesman problem

Vorotnikov

Gumenyuk

Pozdniakov

2017

TAPR

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“…genetic algorithm, particle swarm optimization, ant colony algorithm et al ) are also widely used to plan the flight path. And these methods are improved or combined with other methods to relieve their drawback [9]. Meanwhile, methods based on potential field are utilized to meet the real-time requirements of path re-planning.…”

Section: Introductionmentioning

confidence: 99%

UAV Autonomous Collision Avoidance Method Based on Three-dimensional Dynamic Collision Region Model and Interfered Fluid Dynamical System

Liu¹,

Wang²,

Yao³

2017

dtetr

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Abstract. Aiming at the problem of 3D collision avoidance for unmanned aerial vehicle (UAV), this paper proposed a UAV collision detection, collision decision and path re-planning method. Firstly, traditional methods calculate collision regions using certain threshold value of distance or time. In order to improve the shortcoming of existing methods, this paper considered maneuver information of both UAV and aerial intruder. Models of three-dimensional collision regions were presented. The proposed regions models could be used for UAV to successfully detect collision and make an appropriate collision decision. Secondly, a collision decision method based on the proposed regions and interfered fluid dynamical (IFDS) algorithm was present. UAV autonomously made collision decision by using the proposed regions models, and chose an appropriate maneuverer mode to avoid collision. Then the IFDS algorithm was applied to re-plan UAV's flight path. Finally, the simulation results demonstrate the effectiveness of the presented method.

show abstract

A new vibrational genetic algorithm enhanced with a Voronoi diagram for path planning of autonomous UAV

Cited by 280 publications

References 14 publications

Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm

Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm

Planning the flight routes of the unmanned aerial vehicle by solving the travelling salesman problem

UAV Autonomous Collision Avoidance Method Based on Three-dimensional Dynamic Collision Region Model and Interfered Fluid Dynamical System

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