LineDrone Technology: Landing an Unmanned Aerial Vehicle on a Power Line

Mirallès, François; Hamelin, Philippe; Lambert, Ghislain; Lavoie, Samuel; Pouliot, Nicolas; Montfrond, Matthieu; Montambault, Serge

doi:10.1109/icra.2018.8461250

Cited by 58 publications

(34 citation statements)

References 7 publications

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“…The design of electrical shields for multirotor platforms operating in high voltage power lines has not been properly documented so far. The LineDrone aerial robot presented in [14] employs an aluminum structure that also covers the onboard components, what increases considerably the weight (14 kg). Note that the mass density of carbon fiber and aluminum is 1.5 kg•cm 3 and 2.7 kg•cm 3 , respectively.…”

Section: Comparison Of Resultsmentioning

confidence: 99%

“…The technological challenges are still considerable. First of all, the effect of the electromagnetic interference (EMI) generated by the high voltage power line over the inertial measurement unit (IMU), GNSS (global navigation satellite system) sensors, and other electronic components embedded on the aerial platforms has not been properly documented [14]. Ref.…”

Section: Introductionmentioning

confidence: 99%

“…Although climbing-rolling robots provide longer operation times than aerial robots, the difficulty in their deployment or retrieval from the power line (especially taking into account their weight, that may vary from 10 up to 100 kg [21]) is considerable, whereas the ability of VTOL (vertical take-off and landing) UAVs (unmanned aerial robots) like multirotors, whose weight is typically under 10 kg, reduces significantly the time required to reach the points of interest. Hybrid solutions as the one presented in [14] aim to extend the operation time by incorporating a rolling mechanism that allows the robot to move along the line with lower energy consumption after landing on it.…”

Section: Introductionmentioning

confidence: 99%

“…Reference [15] reports preliminary results and simulations on high electrostatic field applied to a multirotor in laboratory conditions without flying, employing later a X-shaped aluminum frame that models the drone body to evaluate the effect of shielding on the corona discharge. The prototype shown in [14] also incorporates metallic shielding cages to protect the onboard components from the electrical interferences, what increases the weight of the drone (14 kg). However, the design of the shield is not documented.…”

Section: Introductionmentioning

confidence: 99%

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Experimental Evaluation of Aerial Manipulation Robot in Contact With 15 kV Power Line: Shielded and Long Reach Configurations

et al. 2021

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The use of aerial manipulators for the inspection and maintenance of the power grid requires the safe interaction of the robot with high voltage power lines. In order to identify possible faults or malfunctions during the approaching or interaction phases, this paper presents experimental results in a real 15 kV power line, considering four different configurations for the manipulator: 1) aluminum tube attached to the landing gear, 2) robotic arm attached to the multi-rotor base, 3) shielded aerial manipulator, and 4) long reach configuration (insulated). The paper investigates the electromagnetic susceptibility of the autopilot and the electronic speed controllers to the electrostatic discharge (ESD) raised when the manipulator touches the line, causing the momentary failure of the rotors. A model of the electromagnetic effects associated to the interaction with the line is provided, comparing later the effectiveness of the two solutions for the aerial manipulator: shielding, and insulation.

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Section: Comparison Of Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental Evaluation of Aerial Manipulation Robot in Contact With 15 kV Power Line: Shielded and Long Reach Configurations

et al. 2021

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“…In order to address these limitations, several alternative solutions from the field of mobile robotics have emerged: the use of Unmanned Aerial Vehicles (UAVs) [1], [2] and Rolling on Wire (ROW) robots or climbing robots [3], [4]. UAVs have the main advantage over ROW robots in the sense that their design does not need to be adapted to a different scenario (e.g.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based System for Automatic Recognition and Diagnosis of Electrical Insulator Strings

et al. 2019

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This paper presents a complete system for automatic recognition and the diagnosis of electrical insulator strings which efficiently combines different deep learning-based components to build a versatile solution to the automation problem of the power line inspection process. To this aim, the proposed system integrates one component responsible for insulator string segmentation and two components in charge of its diagnosis. The insulator string segmentation component consists of a novel fully convolutional network (FCN) architecture, termed Up-Net, which enhances the capabilities of the state-of-the-art U-Net network by introducing new skip connections at certain levels of the architecture. Furthermore, we propose a second variant of the Up-Net network by training it within a generative adversarial network (GAN) framework. The capabilities of the proposed Up-Net variants are incremented by the application of data augmentation and transfer learning techniques, achieving accurate segmentation of the insulator string elements (i.e., discs and caps). Regarding the insulator string diagnosis, we design a convolutional neural network (CNN) which takes as input the mask generated by the insulator string segmentation component and is capable of identifying the absence of a variable number of discs. The second diagnosis component consists of a novel strategy which integrates a Siamese convolutional neural network (SCNN) designed for modeling the similarity between adjacent discs and allowing the detection of several types of disc defects using the same model. The proposed system has been extensively evaluated in several video sequences from real aerial inspections of high-voltage insulators, showing robust insulator recognition and diagnosis capabilities.

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