A Technical Framework for Selection of Autonomous UAV Navigation Technologies and Sensors

Al-Darraji, Izzat; Derbali, Morched; Jerbi, Houssem; Khan, Fazal Qudus; Jan, Sadeeq; Piromalis, Dimitrios; Tsaramirsis, Georgios

doi:10.32604/cmc.2021.017236

Cited by 21 publications

(6 citation statements)

References 21 publications

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“…The results on the above graph and table have mostly shown liner results, this shows that the result from the simulation is likely to be correct, furthermore in the stress and strain graph three simulations have shown liner results, it proves that under the condition made in the simulations the shell will not reach its yield strength and plastic deformation would not happen under these conditions. As noted in the paper [17], there is currently a high demand for UAVs capable of inspecting outdoor environments. The proposed shell system presented in this paper could prove to be an important solution to mitigate problems associated with deploying drones and sensors in outdoor environments.…”

Section: Discussionmentioning

confidence: 99%

Design of a Shell to Protect Sensors and Drones

Hei,

Kulshrestha,

Randhawa

2023

ICST Transactions on Scalable Information Systems

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This paper presents a novel protective shell system designed to safeguard both the drone and its accompanying sensors. The objective of this project is to develop and test the shell-shaped container to check its capability of securely housing the drone. The system may incorporate a circuit board housing a processor that receives data from sensors and controls the opening and closing motions of the container. By analyzing the sensor information, the system may intelligently respond to adverse weather conditions by automatically closing the container to ensure the drone’s protection. This innovative solution addresses the challenges associated with deploying drones in outdoor environments and offers enhanced safety and durability for extended drone operations.

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Section: Discussionmentioning

confidence: 99%

Design of a Shell to Protect Sensors and Drones

Hei,

Kulshrestha,

Randhawa

2023

ICST Transactions on Scalable Information Systems

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“…Some of these tasks are reaching far distances and working in dangerous regions. Drones can do many tasks with more accuracy than humans due to the ability of integrating various sensor types with the drone platform [86]. For instance, the particularity of equipping infrared and ultraviolet sensors with drones provide the ability of detecting defects precisely in the components of industry.…”

Section: Robots and Dronesmentioning

confidence: 99%

A Modern Approach towards an Industry 4.0 Model: From Driving Technologies to Management

et al. 2022

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Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberphysical systems and Internet of Things (IoT), artificial intelligence (AI), machine learning (ML) and big data, robots and drones, cloud computing, 5G and 6G networks, 3D printing, virtual and augmented reality, and blockchain technology. These technologies are based on a set of foundation technologies which include advances in computing, nanotechnology, biotechnology, materials, energy, and finally cube satellites. We illustrate the confluence of all these technologies in a single model factory. This new factory model succinctly demonstrates the advancements in manufacturing introduced by these modern technologies, which qualifies this as a seminal industrial revolutionary event in human history.

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“…The output gate is also an important gate structure of the long and short memory neural network. It selectively outputs the historical state and the state after the input operation, as shown in Equations ( 11) and (12).…”

Section: ∂E ∂Kmentioning

confidence: 99%

“…As a result, it is believed that the autonomous navigation system of drones can complete a navigation method similar to the homing behavior of pigeons and has high navigation accuracy, a technology worth promoting. Al-Darraji et al [12] believe that the accuracy of autonomous navigation drones depends on the accuracy of sensors, such as image mapping and autonomous obstacle avoidance. At the same time, they suggested that a combination of various sensors should be avoided.…”

Section: Introductionmentioning

confidence: 99%

An Improved Four-Rotor UAV Autonomous Navigation Multisensor Fusion Depth Learning

Liu

et al. 2022

Wireless Communications and Mobile Computing

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Whether it is for military or civilian use, quadrotor UAV has always been one of research central issues. Most of the current quadrotor drones are manually operated and use GPS signals for navigation, which not only limits the operating range of the drone but also consumes a lot of manpower and material resources. This research mainly studies the method of realizing autonomous flight and conflict avoidance of quadrotor UAV by using multisensor system and deep learning method in extreme flight conditions through track prediction. The convolutional neural network method is used to extract the image information collected by the UAV sensor system. And it uses the cyclic neural network to extract the time feature of the information collected by the UAV sensor. The research results show that the track prediction method based on the deep learning method has higher flight accuracy for quadrotor UAVs. The yaw error of the spatial position is only 2.82%, and the maximum error of the time characteristic error tolerance is only 0.77%.

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A Technical Framework for Selection of Autonomous UAV Navigation Technologies and Sensors

Cited by 21 publications

References 21 publications

Design of a Shell to Protect Sensors and Drones

Design of a Shell to Protect Sensors and Drones

A Modern Approach towards an Industry 4.0 Model: From Driving Technologies to Management

An Improved Four-Rotor UAV Autonomous Navigation Multisensor Fusion Depth Learning

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