Game Theory-Based Optimal Cooperative Path Planning for Multiple UAVs

Nguyen, Lanh Van; Phung, Manh Duong; Ha, Q.P.

doi:10.1109/access.2022.3213035

Cited by 15 publications

(7 citation statements)

References 33 publications

(37 reference statements)

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“…where P is the UAV path and ω i for i = 1, 2, ..., 4 are weight coefficients. The traveling distance cost F tr , the safety cost F sa , and the smoothness cost F sm can be found in [10].…”

Section: Path Planningmentioning

confidence: 99%

Monorail bridge inspection using digitally-twinned UAVs

Nguyen,

Le,

Nguyen

et al. 2024

E3S Web Conf.

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This paper introduces a comprehensive approach to monorail bridge inspection utilizing unmanned aerial vehicles (UAVs) and digital twin technology. The autonomous UAV-based inspection design encompasses UAV dynamics, tracking control, path planning, and task execution. A dedicated digital twin platform is developed to facilitate rigorous testing and verification of UAV control, mitigating the necessity for extensive physical testing. Methodology validation is achieved through a combination of simulations and real-world experiments, affirming its efficacy in authentic scenarios and demonstrating the potential for advancing infrastructure inspection practices.

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“…where P is the UAV path and ω i for i = 1, 2, ..., 4 are weight coefficients. The traveling distance cost F tr , the safety cost F sa , and the smoothness cost F sm can be found in [10].…”

Section: Path Planningmentioning

confidence: 99%

Monorail bridge inspection using digitally-twinned UAVs

Nguyen,

Le,

Nguyen

et al. 2024

E3S Web Conf.

View full text Add to dashboard Cite

show abstract

“…An overview of the current UAV path planning strategies is presented in Zhao et al (2021) and Flores-Caballero et al (2020). In literature, there are several different solution alternatives, including exact and heuristic algorithms, such as stochastic heuristics (Sahingoz, 2014;Liu et al, 2019;Van Nguyen et al, 2022;Shao et al, 2022), deterministic heuristics (Mandal et al, 2021;Li et al, 2019), hybridization of stochastic and deterministic heuristics (Geng et al, 2014;Yue and Zhang, 2018;Chen et al, 2022aChen et al, , 2022bZhang et al, 2022;Jia et al, 2022), hybridization of different stochastic heuristics (Cai et al, 2016;Haghighi et al, 2020;Wu et al, 2021), hybridization of heuristics and exact methods (Wang et al, 2014;Shao et al, 2021;Chen et al, 2022aChen et al, , 2022b and exact methods Cheng et al, 2022). There are some drawbacks of these studies, such as straight path constructions (Jia et al, 2022), application on relatively simple problems (Cheng et al, 2022), ignoring real-life constraints, such as obstacle and collision avoidance, which are important for multi-UAV systems (Shao et al, 2022;Mandal et al, 2021;Chen et al, 2022aChen et al, , 2022bWang and Du, 2022;Zhu et al, 2022) and underestimation of altitude limitations (Sahingoz, 2014;Mandal et al, 2021;Zhang et al, 2022;.…”

Section: Related Workmentioning

confidence: 99%

“…In literature, there are several different solution alternatives, including exact and heuristic algorithms, such as stochastic heuristics (Sahingoz, 2014; Liu et al. , 2019; Van Nguyen et al. , 2022; Shao et al.…”

Section: Introductionmentioning

confidence: 99%

An efficient path planning approach for autonomous multi-UAV system in target coverage problems

Pehlivanoglu,

Pehlivanoğlu

2024

AEAT

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Purpose The purpose of this paper is to present an efficient path planning method for the multi-UAV system in target coverage problems. Design/methodology/approach An enhanced particle swarm optimizer (PSO) is used to solve the path planning problem, which concerns the two-dimensional motion of multirotor unmanned aerial vehicles (UAVs) in a three-dimensional environment. Enhancements include an improved initial swarm generation and prediction strategy for succeeding generations. Initial swarm improvements include the clustering process managed by fuzzy c-means clustering method, ordering procedure handled by ant colony optimizer and design vector change. Local solutions form the foundation of a prediction strategy. Findings Numerical simulations show that the proposed method could find near-optimal paths for multi-UAVs effectively. Practical implications Simulations indicate the proposed method could be deployed for autonomous multi-UAV systems with target coverage problems. Originality/value The proposed method combines intelligent methods in the early phase of PSO, handles obstacle avoidance problems with a unique approach and accelerates the process by adding a prediction strategy.

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“…Through cooperation, the population is optimized. Each potential solution of an optimization problem is considered a bird in the search space, called a "particle" [12]. Each particle has a moderate value determined by an objective function and a speed to determine the flight distance and direction.…”

Section: Principles Of Particle Swarm Optimization Planning Algorithmmentioning

confidence: 99%

Research on Automatic Vertical Parking Path Planning Algorithm for Narrow Parking Spaces

Wu,

Li,

Gao

et al. 2023

Preprint

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The narrow parking space will result in difficulties in path planning and spot turning caused by sudden changes and discontinuities in path curvature. To address the problem, this paper investigates the performance of three path planning algorithms and proposes a path optimization algorithm. First, the narrow parking space is defined based on single-step parking of the arc-line combination parking algorithm. Second, to compare the arc-line combination algorithm, Hybrid A* algorithm, and particle swarm optimization parking algorithm under different narrow parking spaces, a multi-objective evaluation function is proposed, including three evaluation indicators, namely, the path length, the number of positive and negative conversions of vehicle speed, and the smoothness of the path. Their performance is compared by simulation conducted in MATLAB, the results show that the Hybrid A* algorithm is the better than others for narrow parking spaces. Third, to smooth the planning path, a path optimization algorithm based on the cubic B-spline curve and gradient descent is proposed. Finally, the simulation is conducted between the proposed algorithm and Hybrid A* algorithm, the result shows that the proposal can effectively eliminate the curvature mutation point and constrain the path curvature to meet the requirements of a smooth path.

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Game Theory-Based Optimal Cooperative Path Planning for Multiple UAVs

Cited by 15 publications

References 33 publications

Monorail bridge inspection using digitally-twinned UAVs

Monorail bridge inspection using digitally-twinned UAVs

An efficient path planning approach for autonomous multi-UAV system in target coverage problems

Research on Automatic Vertical Parking Path Planning Algorithm for Narrow Parking Spaces

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