Pruning tree-branches close to electrical power lines using a skew-gripper and a multirotor helicopter

Molina, Javier; Hirai, Shinichi

doi:10.1109/aim.2017.8014169

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…( ) = log(1 + ) • Mean square error (MSE) is one of the most widely used loss functions, which averages the squared differences between the actual value and predicted value (3). ( , ) = 1⁄ ∑ | − | 2 (3)…”

Section: Cnn Architecturementioning

confidence: 99%

“…Insulator inspection methods, which are extensively used, include standard ground patrolling, and airborne imaging through helicopters. During these procedures, the power lines and their components are observed using optical measuring devices [2,3]. Ground patrolling inspectors perform the visual inspection using different instruments, such as, binoculars, infrared radiation, and ultraviolet (UV) cameras, and identify external defects and the pollution intensity on the outdoor insulators.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Modal Data Fusion Using Deep Neural Network for Condition Monitoring of High Voltage Insulator

et al. 2020

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A novel Fusion Convolutional Network (FCN) is proposed in this research for potential realtime monitoring of insulators using unmanned aerial vehicle (UAV) edge devices. Precise airborne imaging of outdoor objects, such as high voltage insulators, suffers from varied object resolution, cluttered backgrounds, unclear or contaminated surfaces, and illumination conditions. Accurate information about the insulator surface condition is essential and is of a high priority since insulator breakdown is a leading cause of electrical failure. A multi-modal information fusion (MMIF) system is developed during this research to analyze and classify possible contaminations present on the electrical insulators. A novel system, referred to as FCN, consists of a Convolutional Neural Network (CNN) and a binary Multilayer Neural Network (MNN) sub-classifier. While constructing the MMIF dataset for training and testing the novel FCN, the image classification output of the CNN is combined with the leakage current values (LCV) obtained as the classification output of MNN. Each sample of the MMIF dataset is, therefore, represented as a series of fusions. Later, sub-classifiers, of the FCN, are trained to identify the contamination types in the fusion series by implementing a voting system of sub-classifiers which is trained to identify a given class. As a result of the implementation of the proposed FCN, the classification accuracy increased by 8.4%, i.e., from 92% to 99.76%. To compare and benchmark the performance of proposed FCN, conventional classification algorithms are also implemented on the fusion of features that are extracted employing the wavelet transform and PCA methods. State-of-the-art CNN architectures are also discussed on account of their time consumption and memory usage. The conceptualization of a potential hardware implementation of the proposed FCN, on emerging edge devices, is also provided for completeness of the discussion. Pertinent outcomes of this research can be further extended to other potential applications of airborne imaging. INDEX TERMS Convolutional Neural Network, multi-modal information fusion, electrical insulators, unmanned aerial vehicle.

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Section: Cnn Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Modal Data Fusion Using Deep Neural Network for Condition Monitoring of High Voltage Insulator

et al. 2020

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“…Our work is for tree cutting, and several researchers have researched this issue. Molina et al [9,10] developed an aerial robot equipped with a suspension control device for tree barrier cleaning based on a multirotor. e aerial robot must first fly to the vicinity of the branches to be cut, use the suspension manipulator to hang the body on the trunk to be cut, and then turn on the knife and saw to perform cutting operations.…”

Section: Introductionmentioning

confidence: 99%

A Novel Aerial Manipulator with Front Cutting Effector: Modeling, Control, and Evaluation

Yang

Guoxing

et al. 2021

Complexity

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This paper proposes a novel aerial manipulator with front cutting effector (AMFCE) to address the aerial physical interaction (APhI) problem. First, the system uncertainty and external disturbance during the system movement and contact operation are estimated by modeling the entire robot and contact position. Next, based on the established model, the nonlinear disturbance observer (NDO) is used to estimate and compensate the unknown external disturbance of the system and the uncertainty of the model parameters in real time. Then, the nonsingular terminal synovial membrane control method is used to suppress the part that is difficult to estimate. Finally, a controller which is suitable for the movement and operation of the entire system is designed. The controller’s performance is verified through experiments, and the results show that the design, modeling, and control of the entire system can achieve the APhI.

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“…Moreover, the installation position of the cutting tool on the aerial Robot will cause differences in modeling and control. To the best of our knowledge, the pruning tool can be installed on the top [4][5][6], front [7], and bottom of the fuselage [8]. e branches that need to be cut are generally at the crown of the tree.…”

Section: Introductionmentioning

confidence: 99%

ARSS: A Novel Aerial Robot Performs Tree Pruning Tasks

Yang

Chang

et al. 2020

Discrete Dynamics in Nature and Society

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In this article, we present a novel aerial robot with a suspended saw (ARSS) for pruning trees that are close to electric power lines. The Robot’s movement process includes free flight and aerial pruning. We first established a dynamic model and designed a controller based on the Active Disturbance Rejection Control (ADRC) on the model. Aiming at the problem of saw swing and residual oscillation during the free flight movement, we adopt the linear state feedback to design a swing angle controller. Finally, we use Matlab/Simulink and CoppeliaSim for simulation, and the simulation results verify the effectiveness and feasibility of the controller.

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Pruning tree-branches close to electrical power lines using a skew-gripper and a multirotor helicopter

Cited by 9 publications

References 5 publications

Multi-Modal Data Fusion Using Deep Neural Network for Condition Monitoring of High Voltage Insulator

Multi-Modal Data Fusion Using Deep Neural Network for Condition Monitoring of High Voltage Insulator

A Novel Aerial Manipulator with Front Cutting Effector: Modeling, Control, and Evaluation

ARSS: A Novel Aerial Robot Performs Tree Pruning Tasks

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