Dynamic Reallocation Model of Multiple Unmanned Aerial Vehicle Tasks in Emergent Adjustment Scenarios

Tang, Jun; Chen, Xi; Zhu, Xiaomin; Zhu, Feng

doi:10.1109/taes.2022.3195478

Cited by 55 publications

(37 citation statements)

References 28 publications

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“…Since our article is addressing the heterogeneous nature of modern systems, it is important to highlight this research in the literature. The study presented in [ 26 ] focused on coordinating heterogeneous unmanned aerial vehicles with autonomous control, which had the ability to reallocate resources depending on the currently given tasks. The study used historical data and different algorithms for task reallocation.…”

Section: Literature Reviewmentioning

confidence: 99%

A Hybrid Software and Hardware SDN Simulation Testbed

Buzura

Peculea

Iancu

et al. 2023

Sensors

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In recent years, the software-defined networking (SDN) paradigm has been deployed in various types of networks, including wireless sensor networks (WSN), wide area networks (WAN) and data centers. Given the wide range of SDN domain applicability and the large-scale environments where the paradigm is being deployed, creating a full real test environment is a complex and costly task. To address these problems, software-based simulations are employed to validate the proposed solutions before they are deployed in real networks. However, simulations are constrained by relying on replicating previously saved logs and datasets and do not use real time hardware data. The current article addresses this limitation by creating a novel hybrid software and hardware SDN simulation testbed where data from real hardware sensors are directly used in a Mininet emulated network. The article conceptualizes a new approach for expanding Mininet’s capabilities and provides implementation details on how to perform simulations in different contexts (network scalability, parallel computations and portability). To validate the design proposals and highlight the benefits of the proposed hybrid testbed solution, specific scenarios are provided for each design idea. Furthermore, using the proposed hybrid testbed, new datasets can be easily generated for specific scenarios and replicated in more complex research.

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Section: Literature Reviewmentioning

confidence: 99%

A Hybrid Software and Hardware SDN Simulation Testbed

Buzura

Peculea

Iancu

et al. 2023

Sensors

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show abstract

“…In their dynamic scenario, the number of UAVs was changed by randomly removing some UAVs until a single UAV remained. Tang et al proposed task reassignment based on fuzzy C-means clustering and ant colony algorithm to cope with three types of unexpected events [15]. Unexpected events included (i) when a new target is discovered, (ii) when a target is removed due to a sudden change in weather, and (iii) when an initial assignment needs to be adjusted.…”

Section: Related Workmentioning

confidence: 99%

Extensions of Receding Horizon Task Assignment for Area Coverage in Dynamic Environments

Hong

Jung

Kim

et al. 2023

IEEE Trans. Aerosp. Electron. Syst.

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This study presents a task reassignment strategy that can flexibly handle changes in dynamic environments. Most existing studies have only considered static environments where the mission is predetermined and unexpected events do not occur. However, in practice, the environment in which unmanned aerial vehicles perform their mission is complex and includes various pop-up events. Therefore, task reassignment is essential through re-optimization to adjust the previous plan, which is no longer optimal whenever dynamic events occur. The importance of this study is that the modified receding horizon task assignment algorithm is applied for accurate and efficient task reassignment. In addition, this study aims to provide a complete system architecture from operator input to motor commands for autonomous area coverage missions. Reliable performance validation is also performed through various simulations and a challenging outdoor flight experiment with real hardware implementation.

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“…With the rapid advancement and integration of communication and computer technology, the problem of the cooperative formation of surface ships has received increased attention from scholars around the globe. Notably, the study of ship formation systems is of great theoretical value and practical engineering significance because such systems have greater fault tolerance, adaptability, and working efficiency than traditional single ships when confronting complex tasks [1][2].…”

Section: Introductionmentioning

confidence: 99%

Ship Formation Algorithm Based on the Leader–Follower Method

Meng

Chen³

et al. 2023

IEEE Access

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In recent years, marine engineers have increasingly relied on multiship collaborative work to complete complex tasks at sea and improve maritime transport efficiency. Ship formation significantly contributes to the maintenance of stability during multiship-coordinated operations, but establishing the formation structure while ensuring the safety of each ship remains challenging. Therefore, this study proposes an improved leader-follower-based formation algorithm as a solution to this issue. First, the fast marching square method was used for global static path planning. The leader-follower formation control method then enabled the path tracking of the follower ship to the leader ship. Finally, an improved artificial potential field method was used for local collision avoidance, and virtual obstacles were added to improve the situation in which the ship probably entered a local minimum point. The experimental results revealed that the proposed algorithm could plan a route with time, smoothness, and safety advantages for the formation leader and quickly form a stable formation. Notably, the ship can quickly initiate collision avoidance operations when it encounters an obstacle posing a collision risk.INDEX TERMS Artificial potential field method, fast marching square method, formation of ships, leaderfollower method, local collision, path planning.

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Dynamic Reallocation Model of Multiple Unmanned Aerial Vehicle Tasks in Emergent Adjustment Scenarios

Cited by 55 publications

References 28 publications

A Hybrid Software and Hardware SDN Simulation Testbed

A Hybrid Software and Hardware SDN Simulation Testbed

Extensions of Receding Horizon Task Assignment for Area Coverage in Dynamic Environments

Ship Formation Algorithm Based on the Leader–Follower Method

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