Design, Integration and Implementation of an Intelligent and Self-recharging Drone System for Autonomous Power line Inspection

Iversen, Nicolai; Schofield, Oscar Bowen; Cousin, Linda; Ayoub, Naeem; Bögel, Gerd vom; Ebeid, Emad

doi:10.1109/iros51168.2021.9635924

Cited by 42 publications

(30 citation statements)

References 18 publications

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“…Figure 23 (left) shows the linear relationship between the current (from 85 A to 335 A) on the power line and harvested power. This relationship is still linear at the higher primary current (up to 823 A) according to [30]. Moreover, both graphs also show that the simulation line and experiment line are very close to each other.…”

Section: B Charging Circuit Validationsupporting

confidence: 58%

“…A more efficient system is proposed in [29], where the authors managed to extract 350 W from a 700 A power line, but the weight of the magnetic core was up to 7.1 kg. Using a high magnetic flux density, Nicolai et al in [30], [31] developed a very high power density harvester that extracted up to 120 W from an 800 A power line and weighed 1.1 kg (the total mass of the drone is 9.8 kg) based on the theoretical study in [32]. Their system was integrated into a drone and tested on a real power line.…”

Section: Introductionmentioning

confidence: 99%

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Design of a Wireless Drone Recharging Station and a Special Robot End Effector for Installation on a Power Line

et al. 2022

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Drone autonomous operations near power lines are growing steadily and require innovative techniques to keep them on air. This paper presents a novel electromechanical recharging station that can be mounted on energized AC power line to charge the drone battery wirelessly without a need to modify the electrical infrastructure. The work shows a thorough analysis of the electrical and mechanical core components to build a flexible, lightweight and efficient recharging station that can be attached to a robotic arm. The work also discusses the recharging station design and its special robot end effector that mechanically couples the station with an aerial manipulator. Finally, the recharging station has been tested in the lab and in a real power line setup to validate its design and efficiency. The total achieved mass is 2300 grams with a harvesting efficiency of 77% at 250 A primary current.INDEX TERMS Recharging station, energy harvesting, drone, end effector, power line, unmanned aerial vehicle, aerial robotic manipulation.

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Section: B Charging Circuit Validationsupporting

confidence: 58%

Section: Introductionmentioning

confidence: 99%

Design of a Wireless Drone Recharging Station and a Special Robot End Effector for Installation on a Power Line

et al. 2022

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“…The test setup is similar in the two environments, with the main differences being mission and control parameters e.g, the target object and thresholds. The final system testing is presented in the attachment video 1 .…”

Section: Dpu Pynq Setupmentioning

confidence: 99%

“…Automation through drone technology is emerging. Nowadays, drones can be used to automate manual solutions or improve already automated ones and open up opportunities to solve problems in innovative ways [1], [2]. However, system efficiency, weight, and power consumption are some of the core challenges in equipping small and inexpensive drones with the right tools for success in their autonomous operations.…”

Section: Introductionmentioning

confidence: 99%

MPDrone: FPGA-based Platform for Intelligent Real-time Autonomous Drone Operations

Kovari

Ebeid

2021

2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

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AI-based autonomous onboard drone applications are evolving rapidly and demand dedicated hardware resources to perform effectively. Currently, CPUs and GPUs are commonly used to run these applications. This paper presents a novel drone platform called MPDrone based on the cutting-edge MPSoC boards that combine FPGA, CPU, and GPU in a single chip. The proposed platform utilizes the reconfigurable FPGA chip to run heavy AI algorithms and the CPU to execute ROS for processing communication with the drone flight controller and onboard sensors. The paper introduces the design and implementation of the MPDrone platform, which is validated in simulation and real-world testing through an intelligent object detection and landing use case. The testing results proved the applicability of the proposed FPGA-based platform for AI applications.

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“…Breakthrough in research and innovation in Unmanned Aircraft Systems (UASs) has led to a significant increase in the deployment of autonomous Unmanned Aerial Vehicles (UAVs) in the civil airspace. UAVs also referred to as drones, are unmanned aircraft that perform tasks such as surveillance, monitoring, search and rescue, military use, and infrastructure inspections [1]. Security threats to UAVs are typically targeted at the system level, which comprises all functions employed to allow the UAV to operate.…”

Section: Introductionmentioning

confidence: 99%

Security Threats Analysis of the Unmanned Aerial Vehicle System

Jacobsen

Marandi

2021

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)

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Autonomous Unmanned Aerial Vehicles (UAVs) find increasing use in the civil airspace where multi-UAV systems are deployed to perform operations supervised by remote control facilities. Since these multi-UAV systems operate in public locations and connect using open communication standards, it raises significant security concerns. While most UAV designers befittingly deal with the complexity of autonomy, communication, and control, they often ignore to consider system security aspects in the early design phase. To support the security design process of multi-UAV systems, this paper provides an analysis of cybersecurity threats of multi-UAV systems based on the STRIDE model. The identified threats are subsequently linked with a risk assessment to be prioritized according to severity. We conclude by establishing a set of security design recommendations for connected inspection UAVs to contribute with guidance for the design of future multi-UAV systems.

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Design, Integration and Implementation of an Intelligent and Self-recharging Drone System for Autonomous Power line Inspection

Cited by 42 publications

References 18 publications

Design of a Wireless Drone Recharging Station and a Special Robot End Effector for Installation on a Power Line

Design of a Wireless Drone Recharging Station and a Special Robot End Effector for Installation on a Power Line

MPDrone: FPGA-based Platform for Intelligent Real-time Autonomous Drone Operations

Security Threats Analysis of the Unmanned Aerial Vehicle System

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