Heuristic Drone Pathfinding Over Optimized Charging Station Grid

Kilic, Kemal Ihsan; Mostarda, Leonardo

doi:10.1109/access.2021.3134459

Cited by 5 publications

(2 citation statements)

References 39 publications

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“…For example, Raap et al [9] proposed a novel model to achieve search-trajectory planning for a single dynamic target. Kilic and Mostarda [10] proposed a new framework for path planning by optimizing the charging station grid to use a single UAV to reach multiple static ships. To further make the planned path more suitable and realistic for MSR tasks, a weight related to the path based on the time of accident is introduced into the Ant Colony Optimization (ACO) [11].…”

Section: Introductionmentioning

confidence: 99%

An Improved NSGA-II Based on Multi-Task Optimization for Multi-UAV Maritime Search and Rescue under Severe Weather

Huang

et al. 2023

JMSE

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The international trade heavily relies on maritime transportation. Due to the vastness of the ocean, once an accident happens, fast maritime search and rescue (MSR) is a must, as it is of life-and-death matter. Using unmanned air vehicles (UAVs) is an effective approach to completing complex MSR tasks, especially when the environment is dangerous and changeable. However, how to effectively plan paths for multi-UAVs under severe weather, e.g., to rescue the most urgent targets in the shortest time, is a challenging task. In this study, an improved NSGA-II based on multi-task optimization (INSGA-II-MTO) is proposed to plan paths for multi-UAVs in the MSR tasks. In the INSGA-II-MTO, a novel population initialization method is proposed to improve the diversity of an initial population. Further, two tasks are introduced during the execution of the search algorithm. Namely, one assistant task, which solves a simplified MSR problem through multi-task optimization, is implemented to provide necessary evolutional knowledge to a main task that solves an original MSR problem. The performance of the proposed INSGA-II-MTO is compared with other competitors in three MSR scenarios. Experimental results indicate that the proposed algorithm performs best among the compared ones. It is observed that the INSGA-II-MTO can find a set of shorter total paths and handle the most urgent task in the shortest possible time. Therefore, the proposed method is an effective and promising approach to solving multi-UAVs MSR problems to reduce human causalities and property losses.

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Section: Introductionmentioning

confidence: 99%

An Improved NSGA-II Based on Multi-Task Optimization for Multi-UAV Maritime Search and Rescue under Severe Weather

Huang

et al. 2023

JMSE

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show abstract

“…In contrast to the traditional alternating optimization approach, this study adopted the concave-convex procedure and the penalty dual decomposition to solve the optimization problem of flight path and charging planning. Kilic et al established a grid architecture for drone charging stations and integrated the grids with flight route planning [21]. They proposed the shortest path algorithm that fits the grid characteristics of the charging stations.…”

Section: Introductionmentioning

confidence: 99%

A Mission-Oriented Flight Path and Charging Mechanism for Internet of Drones

Huang

Cheng

et al. 2023

Sensors

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In addition to traditional battery exchange services and stationary charging stations, researchers have proposed wireless charging technology, such as decentralized laser charging or drone-to-drone charging in flight, to provide power to drones with insufficient battery electricity. However, the charging methods presented in the literature will inevitably cause drones to wait in line for charging during peak hours and disrupt their scheduled trips when the number of drones grows rapidly in the future. To the best of our knowledge, there have been no integrated solutions for drone flight path and charging planning to alleviate charging congestion, taking into account the different mission characteristics of drones and the charging cost considerations of drone operators. Accordingly, this paper provides adaptive charging options to help drone operators to solve the above-mentioned problems. Drones on ordinary missions can use conventional battery swap services, wired charging stations, or electromagnetic wireless charging stations to recharge their batteries as usual, whereas drones on time-critical missions can choose drone-to-drone wireless charging or decentralized laser charging deployed along the fight paths to charge the batteries of drones in flight. Notably, since fixed-wing drones have larger wing areas to install solar panels, they can also use solar energy to charge during flight if the weather is clear. The simulation results exhibited that the proposed work reduced the power load of the power grid during peak hours, met the charging needs of each individual drone during flight, and cut down the charging costs of drone operators. As a result, an all-win situation for drone operators, drone customers, and power grid operators was achieved.

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Novel Concave Hull-Based Heuristic Algorithm For TSP

Kilic

Mostarda

2022

Oper. Res. Forum

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Heuristic Drone Pathfinding Over Optimized Charging Station Grid

Cited by 5 publications

References 39 publications

An Improved NSGA-II Based on Multi-Task Optimization for Multi-UAV Maritime Search and Rescue under Severe Weather

An Improved NSGA-II Based on Multi-Task Optimization for Multi-UAV Maritime Search and Rescue under Severe Weather

A Mission-Oriented Flight Path and Charging Mechanism for Internet of Drones

Novel Concave Hull-Based Heuristic Algorithm For TSP

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