321 research outputs found

    Path planning for power transmission line inspection robot based on visual obstacle detection

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    A review on the prospects of mobile manipulators for smart maintenance of railway track

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    Inspection and repair interventions play vital roles in the asset management of railways. Autonomous mobile manipulators possess considerable potential to replace humans in many hazardous railway track maintenance tasks with high efficiency. This paper investigates the prospects of the use of mobile manipulators in track maintenance tasks. The current state of railway track inspection and repair technologies is initially reviewed, revealing that very few mobile manipulators are in the railways. Of note, the technologies are analytically scrutinized to ascertain advantages, unique capabilities, and potential use in the deployment of mobile manipulators for inspection and repair tasks across various industries. Most mobile manipulators in maintenance use ground robots, while other applications use aerial, underwater, or space robots. Power transmission lines, the nuclear industry, and space are the most extensive application areas. Clearly, the railways infrastructure managers can benefit from the adaptation of best practices from these diversified designs and their broad deployment, leading to enhanced human safety and optimized asset digitalization. A case study is presented to show the potential use of mobile manipulators in railway track maintenance tasks. Moreover, the benefits of the mobile manipulator are discussed based on previous research. Finally, challenges and requirements are reviewed to provide insights into future research

    Inspection Robot for Power Line

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    Power line cable and insulator inspection and verification procedures require experienced and highly-skilled technicians. These inspections are done with the aid of binoculars and helicopters, where the inspector will be able to visualize points where damaged spots are seen. These traditional methods have several drawbacks: high operational cost, poor blind-area-free inspections and also fails to provide a safe working environment

    Assessing Wind Impact on Semi-Autonomous Drone Landings for In-Contact Power Line Inspection

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    In recent years, the use of inspection drones has become increasingly popular for high-voltage electric cable inspections due to their efficiency, cost-effectiveness, and ability to access hard-to-reach areas. However, safely landing drones on power lines, especially under windy conditions, remains a significant challenge. This study introduces a semi-autonomous control scheme for landing on an electrical line with the NADILE drone (an experimental drone based on original LineDrone key features for inspection of power lines) and assesses the operating envelope under various wind conditions. A Monte Carlo method is employed to analyze the success probability of landing given initial drone states. The performance of the system is evaluated for two landing strategies, variously controllers parameters and four level of wind intensities. The results show that a two-stage landing strategies offers higher probabilities of landing success and give insight regarding the best controller parameters and the maximum wind level for which the system is robust. Lastly, an experimental demonstration of the system landing autonomously on a power line is presented

    Développement et évaluation d'une stratégie d'atterrissage pour drones semi-autonome sur lignes électriques dans différentes conditions de vent

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    Au cours des dernières années, le recours aux drones pour l’inspection des lignes électriques à haute tension s’est répandu en raison de leur efficacité, de leur rentabilité et de leur ca- pacité à atteindre des zones autrement inaccessibles. Cependant, faire atterrir en toute sécurité ces drones sur les lignes électriques, notamment dans des conditions venteuses, constitue un défi majeur. Cette recherche présente un modèle de contrôle semi-autonome pour permettre l’atterrissage sur une ligne électrique à l’aide de la plateforme NADILE (un drone conçu spécifiquement pour l’inspection des lignes électriques) et évalue le fonc- tionnement dans différentes conditions de vent. L’analyse de la probabilité de réussite de l’atterrissage en fonction de l’état initial du drone a été effectuée à l’aide de la méthode de Monte Carlo. Les performances du système ont été évaluées pour deux stratégies d’atter- rissage différentes, divers paramètres de contrôle, et quatre niveaux de vent. Les résultats ont montré qu’une stratégie d’atterrissage en deux étapes donne de meilleures chances de réussite de l’atterrissage et fournissent des indications précieuses sur les paramètres de contrôle optimaux et le niveau maximal de vent pour lequel le système est fiable. Une dé- monstration expérimentale de l’atterrissage autonome du système sur une ligne électrique a également été réalisée

    Motion Planning

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    Motion planning is a fundamental function in robotics and numerous intelligent machines. The global concept of planning involves multiple capabilities, such as path generation, dynamic planning, optimization, tracking, and control. This book has organized different planning topics into three general perspectives that are classified by the type of robotic applications. The chapters are a selection of recent developments in a) planning and tracking methods for unmanned aerial vehicles, b) heuristically based methods for navigation planning and routes optimization, and c) control techniques developed for path planning of autonomous wheeled platforms

    Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

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    Securing a UAV Using Features from an EEG Signal

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    This thesis focuses on an approach which entails the extraction of Beta component of the EEG (Electroencephalogram) signal of a user and uses his/her EEG beta data to generate a random AES (Advanced Encryption Standard) encryption key. This Key is used to encrypt the communication between the UAVs (Unmanned aerial vehicles) and the ground control station. UAVs have attracted both commercial and military organizations in recent years. The progress in this field has reached significant popularity, and the research has incorporated different areas from the scientific domain. UAV communication became a significant concern when an attack on a Predator UAV occurred in 2009, which allowed the hijackers to get the live video stream. Since a UAVs major function depend on its onboard auto pilot, it is important to harden the system against vulnerabilities. In this thesis, we propose a biometric system to encrypt the UAV communication by generating a key which is derived from Beta component of the EEG signal of a user. We have developed a safety mechanism that gets activated in case the communication of the UAV from the ground control station gets attacked. This system was validated on a commercial UAV under malicious attack conditions during which we implement a procedure where the UAV return safely to an initially deployed "home" position

    LASER Tech Briefs, February 1995

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    Topics included in this issue of LASER Tech Briefs are: Electronic Components and Circuits. Electronic Systems, Physical Sciences, Materials, Mechanics, Fabrication, and Mathematics and Information Sciences, an

    The design and intelligent control of an autonomous mobile robot

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    This thesis presents an investigation into the problems of exploration, map building and collision free navigation for intelligent autonomous mobile robots. The project began with an extensive review of currently available literature in the field of mobile robot research, which included intelligent control techniques and their application. It became clear that there was scope for further development with regard to map building and exploration in new and unstructured environments. Animals have an innate propensity to exhibit such abilities, and so the analogous use of artificial neural networks instead of actual neural systems was examined for use as a method of robot mapping. A simulated behaviour based mobile robot was used in conjunction with a growing cell structure neural network to map out new environments. When using the direct application of this algorithm, topological irregularities were observed to be the direct result of correlations within the input data stream. A modification to this basic system was shown to correct the problem, but further developments would be required to produce a generic solution. The mapping algorithms gained through this approach, although more similar to biological systems, are computationally inefficient in comparison to the methods which were subsequently developed. A novel mapping method was proposed based on the robot creating new location vectors, or nodes, when it exceeded a distance threshold from its mapped area. Network parameters were developed to monitor the state of growth of the network and aid the robot search process. In simulation, the combination of the novel mapping and search process were shown to be able to construct maps which could be subsequently used for collision free navigation. To develop greater insights into the control problem and to validate the simulation work the control structures were ported to a prototype mobile robot. The mobile robot was of circular construction, with a synchro-drive wheel configuration, and was equipped with eight ultrasonic distance sensors and an odometric positioning system. It was self-sufficient, incorporating all its power and computational resources. The experiments observed the effects of odometric drift and demonstrated methods of re-correction which were shown to be effective. Both the novel mapping method, and a new algorithm based on an exhaustive mesh search, were shown to be able to explore different environments and subsequently achieve collision free navigation. This was shown in all cases by monitoring the estimates in the positional error which remained within fixed bounds
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