Visual Inspection of the Aircraft Surface Using a Teleoperated Reconfigurable Climbing Robot and Enhanced Deep Learning Technique

Ramalingam, Balakrishnan; Vega-Heredia, Manuel; Elara, Mohan Rajesh; Vengadesh, Ayyalusami; Lakshmanan, Anirudh Krishna; Ilyas, Muhammad; James, Tan Jun Yuan

doi:10.1155/2019/5137139

Cited by 36 publications

(14 citation statements)

References 31 publications

(47 reference statements)

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“…For handling such tasks, a climbing robot needs to maintain manoeuvrability, sufficient adhesion and high payload to weight ratio to successfully accomplish given inspection tasks. The vast majority of climbing robots, independently of the adhesion method (magnetic, pneumatic, gripping etc), are teleoperated under on-off-based adhesion controllers [12,17], without being able to effectively control the level of adhesion. Only a few attempts found in the related literature, have addressed the issue of controlled adhesion for wall climbing robots [6,14,[18][19][20][21][22], thus highlighting the need for advanced control schemes in order to minimize power consumption while satisfying all demanding operation requirements.…”

Section: Background and Motivationmentioning

confidence: 99%

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On the Optimal Adhesion Control of a Vortex Climbing Robot

Papadimitriou

Ανδρικόπουλος

Nikolakopoulos

2021

J Intell Robot Syst

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This article tackles the challenge of negative pressure adhesion control of a Vortex Robotic (VR) platform, which utilizes a modified Electric Ducted Fan (EDF)-based design for successfully adhering to surfaces of variable curvature. The resulting Vortex Actuation (VA) system is estimated through a switching Autoregressive-Moving-Average with eXternal input (ARMAX) identification, for accurately capturing the throttle to adhesion force relationship throughout its operating range. For safe attachment of the robot on a surface, the critical adhesion is modeled based on the geometrical properties of the robotic platform for providing the required reference forces. Within this work, an explicit controller via the use of a Constraint Finite Time Optimal Control (CFTOC) approach is designed in an offline manner, which results in a lookup table realization that ensures overall system stability in all state transitions. In an effort to further improve the tracking response for arbitrary setup orientations, the adhesion control scheme is extended through a switching EMPC framework. The resulting frameworks are tested through both dynamic simulation and experimental sequences involving: a) adhesion control on a rotating test curved surface and, b) adhesion and locomotion sequences on a water pipe.

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Section: Background and Motivationmentioning

confidence: 99%

“…Fig 12. Photographic still showing the VR operating on a water duct cylinder for the evaluation of the switching EMPC adhesion controller and the locomotion control for a given test path…”

mentioning

confidence: 99%

On the Optimal Adhesion Control of a Vortex Climbing Robot

Papadimitriou

Ανδρικόπουλος

Nikolakopoulos

2021

J Intell Robot Syst

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“…Robot-assisted inspection has become more popular in the last decade. It is widely used for various inspection applications, including monitoring built environment defects, power transmission line fault detection, ship hull inspection, industry production management, cleaning applications, and so on, as found in the robotics literature [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Automating the rodent inspection of the false ceiling using robot-assisted technology is an attractive solution.…”

Section: Introductionmentioning

confidence: 99%

“…Aircraft surface inspection using a reconfigurable, teleoperated robot, ’Kiropter’ was reported by Balakrishnan et al The authors developed a reconfigurable vertical climbing robot for reaching limited places, overlapping joints, and the fuselage of the aircraft’s body. Further, they used deep learning for recognizing and classifying the stains, as well as the defects of an aircraft surface [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

AI Enabled IoRT Framework for Rodent Activity Monitoring in a False Ceiling Environment

Ramalingam

Tun²,

Mohan

et al. 2021

Sensors

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Routine rodent inspection is essential to curbing rat-borne diseases and infrastructure damages within the built environment. Rodents find false ceilings to be a perfect spot to seek shelter and construct their habitats. However, a manual false ceiling inspection for rodents is laborious and risky. This work presents an AI-enabled IoRT framework for rodent activity monitoring inside a false ceiling using an in-house developed robot called "Falcon." The IoRT serves as a bridge between the users and the robots, through which seamless information sharing takes place. The shared images by the robots are inspected through a Faster RCNN ResNet 101 object detection algorithm, which is used to automatically detect the signs of rodent inside a false ceiling. The efficiency of the rodent activity detection algorithm was tested in a real-world false ceiling environment, and detection accuracy was evaluated with the standard performance metrics. The experimental results indicate that the algorithm detects rodent signs and 3D-printed rodents with a good confidence level.

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“…One growing trend of applying computer vision technologies is remote visual inspection (RVI) [ 1 , 2 ], where a human inspector inspects a video instead of being physically present on the site. This is very beneficial when the assets to be inspected are difficult to access or in dangerous environments.…”

Section: Introductionmentioning

confidence: 99%

Detection-Based Object Tracking Applied to Remote Ship Inspection

Xie

Stensrud

Skramstad

2021

Sensors

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We propose a detection-based tracking system for automatically processing maritime ship inspection videos and predicting suspicious areas where cracks may exist. This system consists of two stages. Stage one uses a state-of-the-art object detection model, i.e., RetinaNet, which is customized with certain modifications and the optimal anchor setting for detecting cracks in the ship inspection images/videos. Stage two is an enhanced tracking system including two key components. The first component is a state-of-the-art tracker, namely, Channel and Spatial Reliability Tracker (CSRT), with improvements to handle model drift in a simple manner. The second component is a tailored data association algorithm which creates tracking trajectories for the cracks being tracked. This algorithm is based on not only the intersection over union (IoU) of the detections and tracking updates but also their respective areas when associating detections to the existing trackers. Consequently, the tracking results compensate for the detection jitters which could lead to both tracking jitter and creation of redundant trackers. Our study shows that the proposed detection-based tracking system has achieved a reasonable performance on automatically analyzing ship inspection videos. It has proven the feasibility of applying deep neural network based computer vision technologies to automating remote ship inspection. The proposed system is being matured and will be integrated into a digital infrastructure which will facilitate the whole ship inspection process.

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Visual Inspection of the Aircraft Surface Using a Teleoperated Reconfigurable Climbing Robot and Enhanced Deep Learning Technique

Cited by 36 publications

References 31 publications

On the Optimal Adhesion Control of a Vortex Climbing Robot

On the Optimal Adhesion Control of a Vortex Climbing Robot

AI Enabled IoRT Framework for Rodent Activity Monitoring in a False Ceiling Environment

Detection-Based Object Tracking Applied to Remote Ship Inspection

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