Multi-UAVs cooperative control in communication relay

Fu, Xiaowei; Gao, Xiaoguang

doi:10.1109/icspcc.2016.7753600

Cited by 8 publications

(5 citation statements)

References 14 publications

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“…The algorithm is one of the solutions on Single-Source Shortest Path problem (SSSP) with directed or undirected graphs that has edges with non-negative weights (Ma and Mao, 2018). Dijkstra's algorithm follows the greedy approach and finds the optimal path with the least total cost (shortest path from source to destination) (Xiaowei and Xiaoguang, 2016).…”

Section: The Dijkstra Algorithmmentioning

confidence: 99%

Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms

Husain¹,

Zaabi²,

Hildmann³

et al. 2021

Preprint

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With the growing reliability of modern Ad Hoc Networks, it is encouraging to analyze potential involvement of autonomous Ad Hoc agents in critical situations where human involvement could be perilous. One such critical scenario is the Search and Rescue effort in the event of a disaster where timely discovery and help deployment is of utmost importance. This paper demonstrates the applicability of a bio-inspired technique, namely Ant Algorithms (AA), in optimizing the search time for a near optimal path to a trapped victim, followed by the application of Dijkstra's algorithm in the rescue phase. The inherent exploratory nature of AA is put to use for a faster Z. Husain Electrical and Computer Eng.

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Section: The Dijkstra Algorithmmentioning

confidence: 99%

Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms

Husain¹,

Zaabi²,

Hildmann³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…They tested their algorithms on a simulator considering different environment simulators (wind speed and wind direction) and UAV calibration parameters, like battery level and flight duration. Xiaowei and Xiaoguang (2016) study path‐planning and communication‐optimizing problems when a UAV team performs communication relay tasks. Baker et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…They tested their algorithms on a simulator considering different environment simulators (wind speed and wind direction) and UAV calibration parameters, like battery level and flight duration. Xiaowei and Xiaoguang (2016) and communication-optimizing problems when a UAV team performs communication relay tasks. Baker et al (2016) introduce the survivor discovery problem and present their solution, the first example of a continuous factored coordinated Monte Carlo tree search algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

The Use of UAVs in Humanitarian Relief: An Application of POMDP‐Based Methodology for Finding Victims

Bravo

Leiras

Oliveira

2019

Production and Operations Management

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R esearchers have proposed the use of unmanned aerial vehicles (UAVs) in humanitarian relief to search for victims in disaster-affected areas. Once UAVs must search through the entire affected area to find victims, the path-planning operation becomes equivalent to an area coverage problem. In this study, we propose an innovative method for solving such problem based on a Partially Observable Markov Decision Process (POMDP), which considers the observations made from UAVs. The formulation of the UAV path planning is based on the idea of assigning higher priorities to the areas that are more likely to have victims. We applied the method to three illustrative cases, considering different types of disasters: a tornado in Brazil, a refugee camp in South Sudan, and a nuclear accident in Fukushima, Japan. The results demonstrated that the POMDP solution achieves full coverage of disaster-affected areas within a reasonable time span. We evaluate the traveled distance and the operation duration (which were quite stable), as well as the time required to find groups of victims by a detailed multivariate sensitivity analysis. The comparisons with a Greedy Algorithm showed that the POMDP finds victims more quickly, which is the priority in humanitarian relief, whereas the performance of the Greedy focuses on minimizing the traveled distance. We also discuss the ethical, legal, and social acceptance issues that can influence the application of the proposed methodology in practice.

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“…For the problem of multi-UAVs cooperative search under uncertain environment, Wu et al proposed a multi-UAVs autonomous cooperative search control method based on the model predictive control idea [5]. Fu studied the cooperative area search problem of multiple UAVs under communication constraints, and proposed a multi-step optimization path search decision algorithm based on predictive control [6]. Wu and Guo established a UAV area search model based on a twodimensional discrete grid, and proposed a rolling optimization method of search path based on particle swarm optimization algorithm [7].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Area Search Algorithm for Multi-UAVs in Uncertain Battlefield Environment

Zhu¹,

Huang²,

Wang³

et al. 2023

HSET

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Aiming at the problem of multiple unmanned aerial vehicles (UAVs) cooperative area search in uncertain battlefield environment, a multi-UAVs cooperative area search algorithm based on co-evolutionary genetic algorithm (CEGA) is proposed. Firstly, the raster Map and extended Search Probability Map (SPM) model of the task area are constructed, the UAV state model and sensor detection model are established, and the search environment updating method based on the Bayesian criterion is presented. Then, considering the cooperative elements of multi-UAVs, the cooperative area search planning model is established, and based on the rolling optimization idea, the co-evolutionary genetic algorithm with elite retention strategy is used to optimize the solution, and the multi-UAVs cooperative search paths are generated. Through simulation experiments and comparative analysis, the effectiveness of the proposed algorithm is verified.

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Multi-UAVs cooperative control in communication relay

Cited by 8 publications

References 14 publications

Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms

Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms

The Use of UAVs in Humanitarian Relief: An Application of POMDP‐Based Methodology for Finding Victims

Cooperative Area Search Algorithm for Multi-UAVs in Uncertain Battlefield Environment

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