Advances of UAVs toward Future Transportation: The State-of-the-Art, Challenges, and Opportunities

Gupta, Anunay; Afrin, Tanzina; Scully, Evan; Yodo, Nita

doi:10.3390/futuretransp1020019

Cited by 102 publications

(45 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In particular, UAVs are becoming more and more integrated aboveground. Wireless Sensor Networks (WSNs) to improve connectivity, coverage, and quality of service [ 23 ], with the aim to use them as high-altitude aerial base stations, communication relays, or data collectors [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. The problem of data collection from a UAV is mainly addressed in the literature in terms of optimal trajectory planning, but also flight time minimization or methods to wake up the nodes.…”

Section: Introductionmentioning

confidence: 99%

Data Collection from Buried Sensor Nodes by Means of an Unmanned Aerial Vehicle

Cariou

Moiroux-Arvis

Pinet

et al. 2022

Sensors

View full text Add to dashboard Cite

The development of Wireless Underground Sensor Networks (WUSNs) is a recent research axis based on sensor nodes buried a few dozen centimeters deep. The communication ranges are, however, highly reduced due to the high attenuation of electromagnetic waves in soil, leading to issues of data collection. This paper proposes to embed a data collector on an Unmanned Aerial Vehicle (UAV) coming close to each buried sensor node. The whole system was developed (sensor nodes, data collector, gateway) and experimentations were carried out in real conditions. In hovering mode, the measurements on the RSSI levels with respect to the position of the UAV highlight the interest in maintaining a high altitude when the UAV is far from the node. In dynamic mode, the experimental results demonstrate the feasibility of carrying out the data collection task while the UAV is moving. The speed of the UAV has, however, to be adapted to the required time to collect the data. In the case of numerous buried sensor nodes, evolutionary algorithms are implemented to plan the trajectory of the UAV optimally. To the best of our knowledge, this paper is the first one that reports experiment results combining WUSN and UAV technologies.

show abstract

Section: Introductionmentioning

confidence: 99%

Data Collection from Buried Sensor Nodes by Means of an Unmanned Aerial Vehicle

Cariou

Moiroux-Arvis

Pinet

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…[81] proposes a UAV-cloud framework for disaster sensing in disconnected, intermittent, and resource-constrained environments. Other UAV use cases include aerial entertainment [82], agriculture inspection [83], powerline/BS inspection [84], surveillance [85], aerial monitoring [86], radiation monitoring [87], logistics and transportation [88], and localization and mapping [89].…”

Section: G Unmanned Aerial Vehicles (Uavs)mentioning

confidence: 99%

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

et al. 2022

View full text Add to dashboard Cite

The Internet of Things (IoT) has rapidly expanded for a wide range of applications towards a smart future world by connecting everything. As a result, new challenges emerge in meeting the requirements of IoT applications while retaining optimal performance. These challenges may include power consumption, quality of service, localization, security, and accurate modeling and characterization of wireless channel propagation. Among these challenges, the latter is critical to establishing point-to-point wireless communication between the sensors. Channel modeling also varies depending on the features of the surrounding area, which have a direct impact on the propagation of wireless signals. This presents a difficult task for network planners to efficiently design and deploy IoT applications without understanding the appropriate channel model to analyze coverage and predict optimal deployment configurations. As a result, this challenge has attracted considerable interest in academic and industrial communities in recent years. Therefore, this review presents an overview of current breakthroughs in wireless IoT technologies. The challenges in such applications are then briefly reviewed, focusing on wireless channel propagation modeling and characterization. Finally, the study gives a generalized form of commonly used channel models and a summary of recent channel modeling developments for wireless IoT technology. The outcome of this review is expected to provide a new understanding of the propagation behavior of present and future wireless IoT technologies, allowing network engineers to undertake correct planning and deployment in any environment. Additionally, the study may serve as a guideline for future channel modeling and characterization studies.

show abstract

“…Due to the different types of UAVs, these systems have the ability to perform a wide range of applications that are emerging. The most popular configuration of multi-rotors is the quadrotor UAV, which is applied in a variety of aerial fields, e.g., Radoglou-Grammatiski et al, who presented the compilation of the most important applications for precision agriculture using quadrotors [19]; and Gupta et al, who presented the advances of UAVs and the applications in transportation systems [20]. This configuration only presents four motors attached to the mechanical frame generating a limiting power that restricts the fields of use, especially for rescue and transportation tasks.…”

Section: Related Workmentioning

confidence: 99%

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

Recalde

Guevara

Carvajal

et al. 2022

Sensors

View full text Add to dashboard Cite

Accurate trajectory tracking is a critical property of unmanned aerial vehicles (UAVs) due to system nonlinearities, under-actuated properties and constraints. Specifically, the use of unmanned rotorcrafts with accuracy trajectory tracking controllers in dynamic environments has the potential to improve the fields of environment monitoring, safety, search and rescue, border surveillance, geology and mining, agriculture industry, and traffic control. Monitoring operations in dynamic environments produce significant complications with respect to accuracy and obstacles in the surrounding environment and, in many cases, it is difficult to perform even with state-of-the-art controllers. This work presents a nonlinear model predictive control (NMPC) with collision avoidance for hexacopters’ trajectory tracking in dynamic environments, as well as shows a comparative study between the accuracies of the Euler–Lagrange formulation and the dynamic mode decomposition (DMD) models in order to find the precise representation of the system dynamics. The proposed controller includes limits on the maneuverability velocities, system dynamics, obstacles and the tracking error in the optimization control problem (OCP). In order to show the good performance of this control proposal, computational simulations and real experiments were carried out using a six rotary-wind unmanned aerial vehicle (hexacopter—DJI MATRICE 600). The experimental results prove the good performance of the predictive scheme and its ability to regenerate the optimal control policy. Simulation results expand the proposed controller in simulating highly dynamic environments that showing the scalability of the controller.

show abstract

Advances of UAVs toward Future Transportation: The State-of-the-Art, Challenges, and Opportunities

Cited by 102 publications

References 84 publications

Data Collection from Buried Sensor Nodes by Means of an Unmanned Aerial Vehicle

Data Collection from Buried Sensor Nodes by Means of an Unmanned Aerial Vehicle

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

Contact Info

Product

Resources

About