A Novel Monocular-Based Navigation Approach for UAV Autonomous Transmission-Line Inspection

Bian, Jiang; Hui, Xiaolong; Zhao, Xiangmo; Tan, Min

doi:10.1109/iros.2018.8593926

Cited by 42 publications

(21 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, a significant amount of research is addressing this field. Many researchers have applied computer vision techniques for power transmission towers, and insulators recognition [2][3][4][5][6][7][8]. Image processing algorithms are also heavily employed to power lines recognition and tracking [2,[9][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…Many researchers have applied computer vision techniques for power transmission towers, and insulators recognition [2][3][4][5][6][7][8]. Image processing algorithms are also heavily employed to power lines recognition and tracking [2,[9][10][11][12][13][14][15][16][17]. However, in most of these studies, distance to the lines is not measured, and their robustness is challenging.…”

Section: Introductionmentioning

confidence: 99%

“…In [2] a Region-Based Convolutional Neural Network (R-CNN) is used to localization of transmission towers, and their UAV navigation relies on real-time image processing. The authors of [2] claim that "It is the first time to navigate UAV simultaneously utilizing transmission towers and lines".In [9,15] after the quadrotor helicopter is navigated to the start point of inspection manually, the vehicle performs autonomous waypoint flight above power lines. Additionally, a Light Detection and Ranging (LiDAR) sensor detect and reconstruct the power line shape [15].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Tracking Control of Unmanned Aerial Vehicle for Power Line Inspection

Takaya¹,

Ohta²,

Shibayama³

et al. 2022

Motion Planning

View full text Add to dashboard Cite

This work presents some results about power transmission line tracking control and a full autonomous inspection using a quadrotor helicopter. The presented in this paper power line autonomous inspection allows detecting power line defects caused by thunderstorms, corrosion, insulator malfunctions, and same time monitoring of vegetation under the power line corridor. Traditional inspection is performed by helicopters equipped with high-resolution cameras or by direct visual examination carried out by highly skilled staff climbing over de-energized power lines. However, the visual inspection is time-expensive and costly. Moreover, due to regulatory constraints, the helicopters cannot cover narrow mountainous areas. Unmanned aerial vehicles (UAV) are an attractive alternative for power line inspection. In this work, a mathematical model for the quadrotor helicopter used in the autonomous inspection is presented. The model is successfully evaluated through simulations and flight experiments. Next, the construction of a quadrotor helicopter system and its application to power line autonomous inspection is introduced. Simulation and experimental results demonstrate the efficiency and applicability of that system. The results of this research are in the process of implementation for regular inspection of electrical transmission lines.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tracking Control of Unmanned Aerial Vehicle for Power Line Inspection

Takaya¹,

Ohta²,

Shibayama³

et al. 2022

Motion Planning

View full text Add to dashboard Cite

show abstract

“…Widely applied in the field of robotics and automation, visual object tracking aims at predicting the location and size of a target object. Particularly, applying tracking methods onboard unmanned aerial vehicles (UAVs) has facilitated extensive UAV-based applications, e.g., collision avoidance [1], autonomous aerial manipulation operations [2], and autonomous transmission-line inspection [3].…”

Section: Introductionmentioning

confidence: 99%

ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking

Li¹,

Fu²,

Ding³

et al. 2021

Preprint

View full text Add to dashboard Cite

Prior correlation filter (CF)-based tracking methods for unmanned aerial vehicles (UAVs) have virtually focused on tracking in the daytime. However, when the night falls, the trackers will encounter more harsh scenes, which can easily lead to tracking failure. In this regard, this work proposes a novel tracker with anti-dark function (ADTrack). The proposed method integrates an efficient and effective low-light image enhancer into a CF-based tracker. Besides, a target-aware mask is simultaneously generated by virtue of image illumination variation. The target-aware mask can be applied to jointly train a target-focused filter that assists the context filter for robust tracking. Specifically, ADTrack adopts dual regression, where the context filter and the target-focused filter restrict each other for dual filter learning. Exhaustive experiments are conducted on typical dark sceneries benchmark, consisting of 37 typical night sequences from authoritative benchmarks, i.e., UAVDark, and our newly constructed benchmark UAVDark70. The results have shown that ADTrack favorably outperforms other state-of-the-art trackers and achieves a real-time speed of 34 frames/s on a single CPU, greatly extending robust UAV tracking to night scenes.

show abstract

“…On the contrary, the flying PTLIRs use the unmanned aerial helicopters (UAHs) [24][25][26][27][28] or the smart quadrotors [29][30][31][32] to inspect the PTLs. Consequently, these robots provide an alternative in terms of the faster inspection process and the convenient bypass of obstacles as compared to the climbing PTLIRs [33,34].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Aerodynamic Stability of a Lightweight Dual‐Arm Power Transmission Line Inspection Robot under the Influence of Wind

Alhassan

Zhang

Shen

et al. 2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

To efficiently transmit electric power to consumers, the power lines need to be inspected routinely for early fault detection. Thus, power line inspection robots are designed to replace the tedious and dangerous manual inspection using linemen or helicopters. However, most of the existing inspection robots are heavy, which make them slow and prone to external wind disturbance. This paper developed a lightweight dual-arm robot and investigates its robustness to wind disturbance on a lab-scale power line structure. The dynamic equations of the robot are derived using the Lagrangian equation for appropriate motor selection. Also, the components of the robot are designed to ensure low drag coefficient to wind flow, and the mechanism of the wind force on the robot-line coupled system is presented. To study the real-time impact of the wind, a wind speed of 4.5 m/s representing one of the windiest cities in China is considered as a case study. The experimental results for different wind directions, namely, 0°, 45°, and 90°, show that the maximum vibration is 8% higher than the normal vibration of the system in a controlled environment without wind. The results demonstrate that there is little influence of the wind on the system; hence, the robot has been successfully designed and can be applied for power line inspection.

show abstract

A Novel Monocular-Based Navigation Approach for UAV Autonomous Transmission-Line Inspection

Cited by 42 publications

References 19 publications

Tracking Control of Unmanned Aerial Vehicle for Power Line Inspection

Tracking Control of Unmanned Aerial Vehicle for Power Line Inspection

ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking

Investigation of Aerodynamic Stability of a Lightweight Dual‐Arm Power Transmission Line Inspection Robot under the Influence of Wind

Contact Info

Product

Resources

About