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

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

Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 3: ARAMIS overview

An overview of automation, robotics, and machine intelligence systems (ARAMIS) is provided. Man machine interfaces, classification, and capabilities are considered

Power Transmission Lines: Worldwide Research Trends

The importance of the quality and continuity of electricity supply is increasingly evident given the dependence of the world economy on its daily and instantaneous operation. In turn, the network is made up of power transmission lines. This study has been carried out based on the Scopus database, where all the publications, over 5000 documents, related to the topic of the power transmission lines have been analyzed up to the year 2022. This manuscript aims to highlight the main global research trends in power transmission lines and to detect which are the emerging areas. This manuscript cover three main aspects: First, the main scientific categories of these publications and their temporal trends. Second, the countries and affiliations that contribute to the research and their main research topics. Third, identification of the main trends in the field using the detection of scientific communities by means of the clustering method. The three main scientific categories found were Engineering, Energy and Computer Science. This research is most strongly developed in China, as the top 10 institutions are from this country, followed by USA and in third place by Russia. Twelve lines of research have been detected: Line Inspection, Leakage Current, Magnetic Fields, Fault Location, Icing, Lines Design, Natural Disasters, Temperature, Half-wave, Arc Flash, Pattern Recognition, and Artificial Intelligence. This research will open new perspectives for future research on power transmission lines

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets

A survey of electromagnetic influence on uavs from an ehv power converter stations and possible countermeasures

National Natural Science Foundation of China (Grant Nos. 11872148, U1908217, 61801034).It is inevitable that high-intensity, wide-spectrum electromagnetic emissions are generated by the power electronic equipment of the Extra High Voltage (EHV) power converter station. The surveillance flight of Unmanned Aerial Vehicles (UAVs) is thus, situated in a complex electromagnetic environment. The ubiquitous electromagnetic interference demands higher electromagnetic protection requirements from the UAV construction and operation. This article is related to the UAVs patrol inspections of the power line in the vicinity of the EHV converter station. The article analyzes the electromagnetic interference characteristics of the converter station equipment in the surrounding space and the impact of the electromagnetic emission on the communication circuits of the UAV. The anti-electromagnetic interference countermeasures strive to eliminate or reduce the threats of electromagnetic emissions on the UAV’s hardware and its communication network.publishersversionpublishe

Efficient Autonomous Path Planning for Ultrasonic Non-Destructive Testing: A Graph Theory and K-Dimensional Tree Optimisation Approach

Data Availability Statement: Data are contained within the article.Acknowledgements: This work was enabled through the National Structural Integrity Research Centre (NSIRC), a postgraduate engineering facility for industry-led research into structural integrity established and managed by TWI Ltd. through a network of both national and international universities.Within the domain of robotic non-destructive testing (NDT) of complex structures, the existing methods typically utilise an offline robot-path-planning strategy. Commonly, for robotic inspection, this will involve full coverage of the component. An NDT probe oriented normal to the component surface is deployed in a raster scan pattern. Here, digital models are used, with the user decomposing complex structures into manageable scan path segments, while carefully avoiding obstacles and other geometric features. This is a manual process that requires a highly skilled robotic operator, often taking several hours or days to refine. This introduces several challenges to NDT, including the need for an accurate model of the component (which, for NDT inspection, is often not available), the requirement of skilled personnel, and careful consideration of both the NDT inspection method and the geometric structure of the component. This paper addresses the specific challenge of scanning complex surfaces by using an automated approach. An algorithm is presented, which is able to learn an efficient scan path by taking into account the dimensional constraints of the footprint of an ultrasonic phased-array probe (a common inspection method for NDT) and the surface geometry. The proposed solution harnesses a digital model of the component, which is decomposed into a series of connected nodes representing the NDT inspection points within the NDT process—this step utilises graph theory. The connections to other nodes are determined using nearest neighbour with KD-Tree optimisation to improve the efficiency of node traversal. This enables a trade-off between simplicity and efficiency. Next, movement restrictions are introduced to allow the robot to navigate the surface of a component in a three-dimensional space, defining obstacles as prohibited areas, explicitly. Our solution entails a two-stage planning process, as follows: a modified three-dimensional flood fill is combined with Dijkstra’s shortest path algorithm. The process is repeated iteratively until the entire surface is covered. The efficiency of this proposed approach is evaluated through simulations. The technique presented in this paper provides an improved and automated method for NDT robotic inspection, reducing the requirement of skilled robotic path-planning personnel while ensuring full component coverage.This project was part of an initiative known as AEMRI (Advanced Engineering Materials Research Institute), which is funded by the Welsh European Funding Office (WEFO) using European Regional Development Funds (ERDF) WEFO contract no. 80854

Remote Sensing methods for power line corridor surveys

AbstractTo secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments and practical monitoring conditions are needed. These should include careful quality analyses and comparisons between different data sources, methods and individual algorithms

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures