Trajectory Synthesis for a UAV Swarm Based on Resilient Data Collection Objectives

Jakaria, A H M; Rahman, Mohammad Ashiqur; Asif, Muneeba; Khalil, Alvi Ataur; Kholidy, Hisham A.; Anderson, Matthew; Drager, Steven

doi:10.1109/tnsm.2022.3216804

Cited by 14 publications

(5 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The computational cost for generating trajectories in ref. [39] increases exponentially with the number of waypoints. In ref.…”

Section: Simulations Results and Discussionmentioning

confidence: 99%

“…In ref. [39], the navigation paths are subject to several constraints: (i) resilience, where multiple UAVs inspect the same targets to reliably collect data from the necessary points; (ii) data freshness which specifies the time within which a specific number of UAVs must visit a point to ensure no data discrepancy; and (iii) fuel cost which should remain within a budget so that the UAV can reach the destination within a certain time limit. However, our approach does not focus on resiliency and data freshness, but on minimising the total inspection time for emergency-critical events.…”

Section: Simulation Settings and Benchmarkmentioning

confidence: 99%

“…In ref. [39], the authors presented an approach for automatically generating efficient trajectories for a swarm of UAVs with the objective of ensuring that the necessary data points were visited while satisfying resilience, data freshness, fuel usage, and coverage requirements. In ref.…”

Section: Introductionmentioning

confidence: 99%

“…It is worth noting that even though the multi‐UAVs paths optimisation is not a new problem in literature; however, it is novel for the power grid lines inspection. In specific, existing UAV flying path design [20–33, 39, 41, 44, 45] cannot be directly applied to power grid inspection, since the latter should ensure loads are connected to a healthy substation, and should consider load prioritisation, where inspecting the most critical loads first is of utmost importance for fast power restoration. Unfortunately, all the existing works related to UAVs path design for power inspection [12–19, 36, 38, 42] do not consider these important aspects.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Efficient unmanned aerial vehicle paths design for post‐disaster damage assessment of overhead transmission lines

et al. 2023

View full text Add to dashboard Cite

The widespread distribution of overhead transmission lines increases the vulnerability of power grids to failures. Thus, power lines need to be timely inspected, especially before or during emergency‐related situations to ensure stable operation of the power grid. Traditional methods of visual inspection (satellites and helicopters) are inconvenient, often cannot be deployed and if they are deployed present a slow response time and high cost, which is very critical for fast post‐disaster damage identification. On the other hand, employing an unmanned aerial vehicle (UAV) offers a more efficient, reliable, and faster means for the assessment process. This article proposes a novel approach for the post‐disaster UAV‐based damage assessment of overhead power lines. In the proposed approach, the UAVs paths over the most critical loads are formulated as an optimisation problem with the objective of minimising the total inspection time while considering the recharging of the UAVs' batteries. To solve the problem, an efficient framework that optimises the UAVs flight paths is proposed to inspect the critical loads in an efficient order, while accounting for the UAV recharging. This guarantees that the UAVs complete the assessment tasks unlike existing benchmarks.

show abstract

“…The computational cost for generating trajectories in ref. [39] increases exponentially with the number of waypoints. In ref.…”

Section: Simulations Results and Discussionmentioning

confidence: 99%

Section: Simulation Settings and Benchmarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Efficient unmanned aerial vehicle paths design for post‐disaster damage assessment of overhead transmission lines

et al. 2023

View full text Add to dashboard Cite

show abstract

“…A UAV's air-to-ground link covers a wide range, its random deployment is not limited by topography and geomorphology, and it can be used flexibly [1][2][3][4]. It can quickly and efficiently complete dynamic networking [5][6][7] and realize unmanned, networked [8,9], information-based, and intelligent management [10,11], which has attracted the attention of many scholars at home and abroad. These advantages make UAV widely used in various engineering fields such as aviation monitoring, intelligent agriculture, intelligent transportation, emergency rescue and disaster relief, marine patrol, forest fire prevention, and so on [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Energy-Efficient Data Collection Optimization Algorithm for UAV Swarm in the Intelligent Internet of Things

Sun

Cai

Wang

et al. 2023

Drones

View full text Add to dashboard Cite

In the case of limited endurance of unmanned aerial vehicles (UAVs), in order to further improve UAV data collection efficiency, this paper puts forward EDC-UAVIIoT: an enhanced energy-efficient data collection optimization algorithm for UAV swarm in the intelligent Internet of Things. First of all, the algorithm optimizes the UAV cruise path through the intelligent Internet of Things routing mechanism, avoids the occurrence of data errors in the packet transmission process, and uses the end-to-end transmission error probability model. The error probability of data packets in the transmission process is calculated to improve the efficiency of data collection tasks and data throughput. Secondly, considering the relationship between energy harvesting and energy consumption balance, this paper uses semi-definite programming and a convex approximation algorithm to transform the non-convex optimization problem into a convex optimization problem and realize the mapping relationship between the UAV cluster node and the target node coordinates, which reduces the computational complexity. Finally, the simulation results show that the EDC-UAVIIoT algorithm is compared with other algorithms in network energy consumption, running time, network delay, and network throughput. The numerical values are increased by 7.03%, 10.16%, 12.39%, and 8.82%, respectively, thus verifying the effectiveness and stability of the proposed EDC-UAVIIoT algorithm.

show abstract

Deep learning-based energy harvesting with intelligent deployment of RIS-assisted UAV-CFmMIMOs

Khalil

Rahman

2023

Computer Networks

View full text Add to dashboard Cite

Trajectory Synthesis for a UAV Swarm Based on Resilient Data Collection Objectives

Cited by 14 publications

References 45 publications

Efficient unmanned aerial vehicle paths design for post‐disaster damage assessment of overhead transmission lines

Efficient unmanned aerial vehicle paths design for post‐disaster damage assessment of overhead transmission lines

An Enhanced Energy-Efficient Data Collection Optimization Algorithm for UAV Swarm in the Intelligent Internet of Things

Deep learning-based energy harvesting with intelligent deployment of RIS-assisted UAV-CFmMIMOs

Contact Info

Product

Resources

About