Sparse Online Gaussian Process Adaptive Control of Unmanned Aerial Vehicle with Slung Payload DOI Creative Commons
Muhammed Rasit Kartal, Dmitry Ignatyev, Argyrios Zolotas

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(11), P. 687 - 687

Published: Nov. 19, 2024

In the past decade, Unmanned Aerial Vehicles (UAVs) have garnered significant attention across diverse applications, including surveillance, cargo shipping, and agricultural spraying. Despite their widespread deployment, concerns about maintaining stability safety, particularly when carrying payloads, persist. The development of such UAV platforms necessitates implementation robust control mechanisms to ensure stable precise maneuvering capabilities. Numerous operations require integration which introduces substantial challenges. Notably, involving unstable payloads as liquid or slung pose a considerable challenge in this regard, falling into category mismatched uncertain systems. This study focuses on establishing for payload-carrying Our approach involves combination various algorithms: incremental backstepping algorithm (IBKS), integrator (IBS), Proportional–Integral–Derivative (PID), Sparse Online Gaussian Process (SOGP), machine learning technique that identifies mitigates disturbances. With comparison linear nonlinear methodologies through different scenarios, an investigation effective solution has been performed. Implementation component, employing SOGP, effectively detects counteracts Insights are discussed within remit rejecting sloshing disturbance.

Language: Английский

Cost Efficiency and Effectiveness of Drone Applications in Bridge Condition Monitoring DOI Creative Commons
Taraneh Askarzadeh, Raj Bridgelall

Infrastructures, Journal Year: 2025, Volume and Issue: 10(3), P. 63 - 63

Published: March 13, 2025

Bridges are an integral and important part of road networks, but monitoring their condition using traditional methods is expensive, dangerous, laborious. This study examines the rapidly emerging field drone-based transportation asset monitoring, focusing on analyzing cost efficiency effectiveness drone applications in bridge monitoring. research innovated a multi-dimensional framework that highlights transformative role technology enhancing inspection accuracy, safety, savings. Using statistical models Monte Carlo simulations, provides extensive cost–benefit analysis to inform investment decisions. A case demonstrates utility quantifying costs benefits. Furthermore, sensitivity evaluates how variations costs, driven by technological progress, can potentially influence adoption technology.

Language: Английский

Citations

0
A Review of Physical Layer Security in Aerial–Terrestrial Integrated Internet of Things: Emerging Techniques, Potential Applications, and Future Trends DOI Creative Commons
Yixin He, Jingwen Wu, Lijun Zhu

et al.

Drones, Journal Year: 2025, Volume and Issue: 9(4), P. 312 - 312

Published: April 16, 2025

The aerial–terrestrial integrated Internet of Things (ATI-IoT) utilizes both aerial platforms (e.g., drones and high-altitude platform stations) terrestrial networks to establish comprehensive seamless connectivity across diverse geographical regions. integration offers significant advantages, including expanded coverage in remote underserved areas, enhanced reliability data transmission, support for various applications such as emergency communications, vehicular ad hoc networks, intelligent agriculture. However, due the inherent openness wireless channels, ATI-IoT faces potential network threats attacks, its security issues cannot be ignored. In this regard, incorporating physical layer techniques into is essential ensure integrity confidentiality. Motivated by aforementioned factors, review presents latest advancements that facilitate security. Specifically, we elucidate endogenous safety upon which illustrate current status architectures along with functions their components. Subsequently, emerging reflective surfaces-assisted device-to-device covert cooperative transmissions) enabling are demonstrated categorized based on technical principles. Furthermore, given offer flexible deployment high re-positioning capabilities, discussions practical provided. Finally, several unresolved pertaining challenges well sustainability concerns outlined.

Language: Английский

Citations

0
Role of Drones in Climate Change Mitigation and Adaptation DOI
Sameer Saharan,

Meha Khiria,

Tilak Ram Chandrakar

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 41 - 70

Published: Feb. 28, 2025

In this chapter, important benefits of drone technology have been discussed which can significantly increase climate flexibility. Unmatched capacity is provided by drones in areas risk assessment, environmental monitoring, concerns and quick action. Their high height, advanced sensor favorable viewing places are the reason for this. The use provides information necessary to make initial intervention program construction informed decisions. Two examples applications under category include tracking forest cutting altering sea-mounting level. Adopting help many ways, such as increasing community adaptability, reducing effects change advancing continuous development. purpose chapter provide an in-depth analysis potential shortcomings, advantages useful tools development flexible civilizations towards change.

Language: Английский

Citations

0
Connectivity Preservation and Obstacle Avoidance Control for Multiple Quadrotor UAVs with Limited Communication Distance DOI Creative Commons

Xianghong Xue,

Bin Yuan, Yingmin Yi

et al.

Drones, Journal Year: 2025, Volume and Issue: 9(2), P. 136 - 136

Published: Feb. 12, 2025

This paper studies the distributed formation control problem for multiple unmanned aerial vehicles (UAVs), focusing on preserving connectivity and avoiding obstacles within constraints of a limited communication distance in presence dynamic obstacles. The UAV network is modeled as proximity graph, where edges are defined by distances between UAVs. A hierarchical strategy employed to manage position attitude subsystems independently. controller developed subsystems, utilizing bounded artificial potential functions preserve avoid collisions UAVs while achieving desired formation. also integrates time-varying sliding manifold obstacle avoidance prevent with Additionally, an designed subsystem track angles generated positioning subsystem. Numerical simulations validate that proposed controllers effectively network’s connectivity, obstacles, achieve simultaneously.

Language: Английский

Citations

0
Drones for Road Condition Monitoring: Applications and Benefits DOI
Taraneh Askarzadeh, Raj Bridgelall,

Denver Tolliver

et al.

Journal of Transportation Engineering Part B Pavements, Journal Year: 2024, Volume and Issue: 151(1)

Published: Nov. 26, 2024

Language: Английский

Citations

1
Sparse Online Gaussian Process Adaptive Control of Unmanned Aerial Vehicle with Slung Payload DOI Creative Commons
Muhammed Rasit Kartal, Dmitry Ignatyev, Argyrios Zolotas

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(11), P. 687 - 687

Published: Nov. 19, 2024

In the past decade, Unmanned Aerial Vehicles (UAVs) have garnered significant attention across diverse applications, including surveillance, cargo shipping, and agricultural spraying. Despite their widespread deployment, concerns about maintaining stability safety, particularly when carrying payloads, persist. The development of such UAV platforms necessitates implementation robust control mechanisms to ensure stable precise maneuvering capabilities. Numerous operations require integration which introduces substantial challenges. Notably, involving unstable payloads as liquid or slung pose a considerable challenge in this regard, falling into category mismatched uncertain systems. This study focuses on establishing for payload-carrying Our approach involves combination various algorithms: incremental backstepping algorithm (IBKS), integrator (IBS), Proportional–Integral–Derivative (PID), Sparse Online Gaussian Process (SOGP), machine learning technique that identifies mitigates disturbances. With comparison linear nonlinear methodologies through different scenarios, an investigation effective solution has been performed. Implementation component, employing SOGP, effectively detects counteracts Insights are discussed within remit rejecting sloshing disturbance.

Language: Английский

Citations

0