A Point-Line-Based SLAM Framework for UAV Close Proximity Transmission Tower Inspection

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

doi:10.1109/robio.2018.8664716

Cited by 14 publications

(12 citation statements)

References 20 publications

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“…A 3D point cloud is estimated from the monocular images at each algorithm interaction, providing the capability to calculate the distance from the UAV and the pylon. The results present an average position error of 0.72 m [5].…”

Section: Related Workmentioning

confidence: 91%

Artificial Intelligence Architecture Based on Planar LiDAR Scan Data to Detect Energy Pylon Structures in a UAV Autonomous Detailed Inspection Process

Ferraz

Júnior

Komori

et al. 2021

Communications in Computer and Information Science

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The technological advances in Unmanned Aerial Vehicles (UAV) related to energy power structure inspection are gaining visibility in the past decade, due to the advantages of this technique compared with traditional inspection methods. In the particular case of power pylon structure and components, autonomous UAV inspection architectures are able to increase the efficacy and security of these tasks. This kind of application presents technical challenges that must be faced to build real-world solutions, especially the precise positioning and path following for the UAV during a mission. This paper aims to evaluate a novel architecture applied to a power line pylon inspection process, based on the machine learning techniques to process and identify the signal obtained from a UAV-embedded planar Light Detection and Ranging -LiDAR sensor. A simulated environment built on the GAZEBO software presents a first evaluation of the architecture. The results show an positive detection accuracy level superior to 97% using the vertical scan data and 70% using the horizontal scan data. This accuracy level indicates that the proposed architecture is proper for the development of positioning algorithms based on the LiDAR scan data of a power pylon.

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Section: Related Workmentioning

confidence: 91%

Artificial Intelligence Architecture Based on Planar LiDAR Scan Data to Detect Energy Pylon Structures in a UAV Autonomous Detailed Inspection Process

Ferraz

Júnior

Komori

et al. 2021

Communications in Computer and Information Science

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“…Reference [11] introduces a least-squares optimization-based alternative. More recently, we have experienced a revival of hybrid feature-based methods, with [12]- [15] providing monocular solutions, [16] a solution for RGB-D cameras, and [17], [18] alternatives for stereo cameras. Reference [19] proposes an extension to a popular direct point-based method [20] by utilizing lines to guide keypoint selection rather than to directly act as features.…”

Section: Related Workmentioning

confidence: 99%

Accurate Line-Based Relative Pose Estimation With Camera Matrices

Wang

Wang³

et al. 2020

IEEE Access

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While most monocular structure-from-motion frameworks rely on sparse keypoints, it has long been acknowledged that lines represent an alternative, higher-order feature with high accuracy, repeatability, and abundant availability in man-made environments. Its exclusive use, however, is severely complicated by its inability to resolve the common bootstrapping scenario of two-view geometry. Even with stereo cameras, a one-dimensional disparity space, as well as ill-posed triangulations of horizontal lines make the realization of purely line-based tracking pipelines difficult. The present paper successfully leverages the redundancy in camera matrices to alleviate this shortcoming. We present a novel stereo trifocal tensor solver and extend it to the case of two camera matrix view-points. Our experiments demonstrate superior behavior with respect to both 2D-2D and 3D-3D alternatives. We furthermore outline the camera matrix's ability to continuously and robustly bootstrap visual motion estimation pipelines via integration into a robust, purely line-based visual odometry pipeline. The result leads to state-of-the-art tracking accuracy comparable to what is achieved by point-based stereo or even dense depth camera alternatives.INDEX TERMS Light-field cameras, multi-camera arrays, plenoptic vision, line features, trifocal tensor, automatic solver generator, Gröbner basis. 1 We define a camera matrix to be a square grid arrangement of perspective cameras. It may also be described as a light-field camera or multi-camera array.

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“…The work [1] proposes a "Point-Line-Based SLAM" technique to provide a center tower position based on image processing. The system uses two highperformance GPU hardware embedded on the UAV to visual information processing.…”

Section: Background and Related Workmentioning

confidence: 99%

Proposal of an Augmented Reality Tag UAV Positioning System for Power Line Tower Inspection

Cantieri

Wehrmeister

Oliveira

et al. 2019

Advances in Intelligent Systems and Computing

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Autonomous inspection Unmanned Aerial Vehicle systems are an essential research area, including power line distribution inspection. Considerable efforts to solve the demanding presented in the autonomous U AV inspection process are present in technical and scientific research. One of these challenges is the precise positioning and fly control of the U AV around the energy structures, which is vital to assure the security of the operation. The most common techniques to achieve precise positioning in UAV fly are Global Positioning Systems with Real-Time Kinematic. This technique demands a proper satellite signal receiving to work appropriately, sometimes hard to achieve. The present work proposes a complementary position data system based on augmented reality tags (AR Tags) to increase the reliability of the UAV fly positioning system. The system application is proposed for energy power tower inspections as an example of use. The adaptation to other inspection tasks is possible whit some small changes. Experimental results have shown that an increase in the position accuracy is accomplished with the use of this schema.

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A Point-Line-Based SLAM Framework for UAV Close Proximity Transmission Tower Inspection

Cited by 14 publications

References 20 publications

Artificial Intelligence Architecture Based on Planar LiDAR Scan Data to Detect Energy Pylon Structures in a UAV Autonomous Detailed Inspection Process

Artificial Intelligence Architecture Based on Planar LiDAR Scan Data to Detect Energy Pylon Structures in a UAV Autonomous Detailed Inspection Process

Accurate Line-Based Relative Pose Estimation With Camera Matrices

Proposal of an Augmented Reality Tag UAV Positioning System for Power Line Tower Inspection

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