scholarly journals A Psychoacoustic Approach to Building Knowledge about Human Response to Noise of Unmanned Aerial Vehicles

2021 ◽  
Vol 18 (2) ◽  
pp. 682
Author(s):  
Antonio J. Torija ◽  
Charlotte Clark
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Noise Exposure ◽  
Autonomous Systems ◽  
Public Health Issue ◽  
Human Response ◽  
Noise Sources ◽  
Governmental Agencies ◽  
Aerial Vehicles ◽  
Operational Characteristics ◽  
Significant Public Health

We are on the cusp of a revolution in the aviation sector, driven by the significant progress in electric power and battery technologies, and autonomous systems. Several industry leaders and governmental agencies are currently investigating the use of Unmanned Aerial Vehicles (UAVs), or “drones” as commonly known, for an ever-growing number of applications—from blue light services to parcel delivery and urban mobility. Undoubtedly, the operation of UAVs will lead to noise exposure, which has the potential to become a significant public health issue. This paper first describes the main acoustic and operational characteristics of UAVs, as an unconventional noise source compared to conventional civil aircraft. Gaps in the literature and the regulations on the noise metrics and acceptable noise levels are identified and discussed. The state-of-the-art evidence on human response to aircraft and other environmental noise sources is reviewed and its application for UAVs discussed. A methodological framework is proposed for building psychoacoustic knowledge, to inform systems and operations development to limit the noise impact on communities.

scholarly journals A Semi-Physical Platform for Guidance and Formations of Fixed-Wing Unmanned Aerial Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1136 ◽  
Author(s):  
Jun Yang ◽  
Arun Geo Thomas ◽  
Satish Singh ◽  
Simone Baldi ◽  
Ximan Wang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Formation Control ◽  
Physical Simulation ◽  
3D Visualization ◽  
Autonomous Systems ◽  
Level Control ◽  
Control Laws ◽  
Ongoing Research ◽  
Control Loops ◽  
Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) have multi-domain applications, fixed-wing UAVs being a widely used class. Despite the ongoing research on the topics of guidance and formation control of fixed-wing UAVs, little progress is known on implementation of semi-physical validation platforms (software-in-the-loop or hardware-in-the-loop) for such complex autonomous systems. A semi-physical simulation platform should capture not only the physical aspects of UAV dynamics, but also the cybernetics aspects such as the autopilot and the communication layers connecting the different components. Such a cyber-physical integration would allow validation of guidance and formation control algorithms in the presence of uncertainties, unmodelled dynamics, low-level control loops, communication protocols and unreliable communication: These aspects are often neglected in the design of guidance and formation control laws for fixed-wing UAVs. This paper describes the development of a semi-physical platform for multi-fixed wing UAVs where all the aforementioned points are carefully integrated. The environment adopts Raspberry Pi’s programmed in C++, which can be interfaced to standard autopilots (PX4) as a companion computer. Simulations are done in a distributed setting with a server program designed for the purpose of routing data between nodes, handling the user inputs and configurations of the UAVs. Gazebo-ROS is used as a 3D visualization tool.

Examination of spectral content, peak frequency relationships, and annoyance for unmanned aerial vehicle operations

2021 ◽  
Vol 263 (4) ◽  
pp. 2767-2776
Author(s):  
Judy Rochat ◽  
Herb Singleton ◽  
Keith Yoerg
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Air Conditioning ◽  
Peak Frequency ◽  
Noise Sources ◽  
Spectral Content ◽  
Lawn Care ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Relationship Of ◽  
The Relationship

Unmanned aerial vehicles (UAVs) can be used for many purposes, servicing delivery, recreational, utility inspection, and film industries, among others. For some applications, use of UAVs can expose communities to a type of noise not currently experienced, with current noise sources typically related to transportation operations (e.g., aircraft, rail, road noise sources) and home activities (e.g., air conditioning units, lawn care). As such, it is important to understand the type of noise communities will experience with UAV operations. For this paper, a UAV flyover event and hover event are examined in terms of spectral content and the relationship of peak frequencies. In addition, the peak frequencies and relationships are discussed in terms of those typically associated with annoyance.

scholarly journals METHODS AND MEANS OF COUNTERACTION OF ACOUSTIC AND OPTICAL RECONNAISSANCE UAV

2020 ◽  
Vol 6 (1) ◽  
pp. 149-154
Author(s):  
Nikita V. Ignatenko ◽  
Alexey N. Polikanin
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
Autonomous Systems ◽  
Multiple Objects ◽  
Multiple Sensors ◽  
Aerial Vehicles ◽  
Main Computer ◽  
Computer Attacks ◽  
Control Technologies ◽  
Combining Information

For the last few years, the ease of purchasing and using unmanned aerial vehicles (UAVs), their affordable cost has increased the demand for them both by companies and individuals. However, these devices might carry out illegal actions, starting with smuggling of illegal goods, unauthorized intelligence and computer attacks. As a result, this led to the urgency of developing effective and available countermeasures to detect and neutralize drones that perform reconnaissance of objects with confidential information. The most successful are autonomous systems for detecting and suppressing drones, which include optoelectronic, acoustic radar and radio frequency sensors, information from which is combined on the main computer to identify the threat and make further decisions. However, real-time monitoring is a rather difficult process that requires timely detection of adverse events or conditions. This creates many complex tasks such as object detection, classification, tracking multiple objects, and combining information from multiple sensors. In recent years, researchers have used various techniques to solve these problems and made notable progress. Applying deep learning to detect and classify UAVs is considered a new concept. In this regard, it became necessary to provide a generalized overview of UAV control technologies used for reconnaissance.

scholarly journals Generic Component-Based Mission-Centric Energy Model for Micro-Scale Unmanned Aerial Vehicles

Drones ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 63
Author(s):  
Christoph Steup ◽  
Simon Parlow ◽  
Sebastian Mai ◽  
Sanaz Mostaghim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Autonomous Systems ◽  
Energy Model ◽  
Generic Model ◽  
Extended Model ◽  
Generic Models ◽  
Aerial Vehicles ◽  
Proposed Model ◽  
Typical Behaviour ◽  
Set Up

The trend towards the usage of battery-electric unmanned aerial vehicles needs new strategies in mission planning and in the design of the systems themselves. To create an optimal mission plan and take appropriate decisions during the mission, a reliable, accurate and adaptive energy model is of utmost importance. However, most existing approaches either use very generic models or ones that are especially tailored towards a specific UAV. We present a generic energy model that is based on decomposing a robotic system into multiple observable components. The generic model is applied to a swarm of quadcopters and evaluated in multiple flights with different manoeuvres. We additionally use the data from practical experiments to learn and generate a mission-agnostic energy model which can match the typical behaviour of our quadcopters such as hovering; movement in x, y and z directions; landing; communication; and illumination. The learned energy model concurs with the overall energy consumption with an accuracy over 95% compared to the training flights for the indoor use case. An extended model reduces the error to less than 1.4%. Consequently, the proposed model enables an estimation of the energy used in flight and on the ground, which can be easily incorporated in autonomous systems and enhance decision-making with reliable input. The used learning mechanism allows to deploy the approach with minimal effort to new platforms needing only some representative test missions, which was shown using additional outdoor validation flights with a different quadcopter of the same build and the originally trained models. This set-up increased the prediction error of our model to 4.46%.

scholarly journals Integrating Comprehensive Human Oversight in Drone Deployment: A Conceptual Framework Applied to the Case of Military Surveillance Drones

Information ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 385
Author(s):  
Ilse Verdiesen ◽  
Andrea Aler Tubella ◽  
Virginia Dignum
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Intelligent Systems ◽  
Autonomous Systems ◽  
Critical Question ◽  
Critical Gap ◽  
Technical Requirements ◽  
A Value ◽  
Aerial Vehicles ◽  
Human Responsibility ◽  
Technical Framework

Accountability is a value often mentioned in the debate on intelligent systems and their increased pervasiveness in our society. When focusing specifically on autonomous systems, a critical gap emerges: although there is much work on governance and attribution of accountability, there is a significant lack of methods for the operationalisation of accountability within the socio-technical layer of autonomous systems. In the case of autonomous unmanned aerial vehicles or drones—the critical question of how to maintain accountability as they undertake fully autonomous flights becomes increasingly important as their uses multiply in both the commercial and military fields. In this paper, we aim to fill the operationalisation gap by proposing a socio-technical framework to guarantee human oversight and accountability in drone deployments, showing its enforceability in the real case of military surveillance drones. By keeping a focus on accountability and human oversight as values, we align with the emphasis placed on human responsibility, while requiring a concretisation of what these principles mean for each specific application, connecting them with concrete socio-technical requirements. In addition, by constraining the framework to observable elements of pre- and post-deployment, we do not rely on assumptions made on the internal workings of the drone nor the technical fluency of the operator.

scholarly journals Application of UAVs for assessment of bridge infrastructure

2021 ◽  
Vol 73 (11) ◽  
pp. 1095-1106
Keyword(s):  
Unmanned Aerial Vehicles ◽  
State Of The Art ◽  
Autonomous Systems ◽  
Transport Infrastructure ◽  
Life Estimation ◽  
Advantages And Disadvantages ◽  
Aerial Vehicles ◽  
Bridge Inspections ◽  
Service Life Estimation ◽  
Structural Inspection

The shortcomings of classical methods for inspection of transport infrastructure objects have led to the development of more efficient, more reliable, faster and cheaper procedures for condition assessment and load-bearing capacity and service life estimation of objects. In this context, different autonomous systems developed in the last decade have the most notable role and their development is continuously speeding up. This paper provides a state of the art review of the unmanned aerial vehicles application for structural inspection with a focus on bridges. The paper comprises the following: a review of the current regulations prescribing the types and frequency of inspections; a review of the current classical inspection methods with their advantages and disadvantages; analysis of advantages and disadvantages in application of unmanned aerial vehicles for bridge inspections and a review of the equipment commonly used in their development.

Development of thickened semi-synthetic engine oil M-5z / 20 AERO for four-stroke gasoline engines aircraft piston of unmanned aerial vehicles (UAVs)

2020 ◽  
Vol 06 ◽  
pp. 44-47
Author(s):  
A.A. Moykin ◽  
◽  
A.S. Medzhibovsky ◽  
S.A. Kriushin ◽  
M.V. Seleznev ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Engine Oil ◽  
Motor Oil ◽  
Gasoline Engines ◽  
State Research Institute ◽  
Technical Requirements ◽  
Aerial Vehicles ◽  
State Research ◽  
Industrial Batch ◽  
The Russian Federation

Nowadays, the creation of remotely-piloted aerial vehicles for various purposes is regarded as one of the most relevant and promising trends of aircraft development. FAU "25 State Research Institute of Chemmotology of the Ministry of Defense of the Russian Federation" have studied the operation features of aircraft piston engines and developed technical requirements for motor oil for piston four-stroke UAV engines, as well as a new engine oil M-5z/20 AERO in cooperation with NPP KVALITET, LLC. Based on the complex of qualification tests, the stated operational properties of the experimental-industrial batch of M-5z/20 AERO oil are generally confirmed.

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