Browsing by Author "Rahimi, Masoumeh"

Now showing 1 - 6 of 6
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    An autonomous rail-road amphibious robotic system for railway maintenance using sensor fusion and mobile manipulator
    (Elsevier, 2023-08-02) Liu, Haochen; Rahman, Miftahur; Rahimi, Masoumeh; Starr, Andrew; Durazo-Cardenas, Isidro; Ruiz-Carcel, Cristobal; Ompusunggu, Agusmian; Hall, Amanda; Anderson, Robert
    The current maintenance of railway infrastructure replies heavily on human involvement, requiring possession of the track section during maintenance, resulting in high costs and inefficient execution. This paper proposes an autonomous rail-road amphibious robotic system for railway inspection and maintenance tasks. By virtue of its road and rail-autonomous mobility, it is able to execute the complete maintenance execution flow in multiple phases. The system provides flexible track job location access, low-cost maintenance execution, and reduced track network possession. The payload mobile manipulator and sensor fusion enhance the system's capabilities for multiple types of inspection and repair. The design of a command and control system was guided by a rule-based expert system strategy to enable remote operation of the whole system. The developed demonstrator of a track wheel accompanied unmanned ground vehicle was integrated and demonstrated in both operational and realistic track environments with multiple testing activities of remote operation, navigation, accurate job detection, inspection, and repair, confirming effective job completion and logical human interaction. The proposed method produces an outstanding hardware-software integrated robotic inspection and repair system with a high level of technological readiness for autonomous railway maintenance and intelligent railway asset management.
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    Challenges for a railway inspection and repair system from railway infrastructure
    (IEEE, 2023-01-16) Rahman, Miftahur; Rahimi, Masoumeh; Starr, Andrew; Durazo-Cardenas, Isidro; Hall, Amanda; Anderson, Robert
    Robots and automation techniques are used in many industries for a long period because of the economic advantages and efficiency. Though the railway has a long history compared to other transportation systems, it still lacks wide application of modern technologies such as robots and AI. Track maintenance using robotic technologies has gained some attraction from both infrastructure managers and researchers due to safety and cost benefits. A Railway Inspection and Repair System (RIRS) has been proposed using commercially available Unmanned Ground Vehicles (UGV) and an industrial manipulator for the railway track inspection and repair tasks. The use of a specially designed trolley enables the on-track and off-track navigation capability of RIRS. The infrastructure in railway is very diversified and unique in size, shape, and remoteness compared to other industries. This research investigates the unique challenges to the operation of RIRS imposed by the railway infrastructure.
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    Investigating precision and accuracy of a robotic inspection and repair system
    (SSRN, 2021-10-20) Rahman, Miftahur; Liu, Haochen; Rahimi, Masoumeh; Ruiz Carcel, Cristobal; Kirkwood, Leigh; Durazo-Cardenas, Isidro; Starr, Andrew
    Robot integration in railway maintenance steps a prominent pavement in high-efficient and low-cost job execution for the infrastructure management. To achieve practical and diverse inspection and repair railway job, a robot manipulator on a locomotive platform is one of the best options. A lot of research has been conducted to find the accuracy and precision of industrial robotic manipulator where the manipulator base is fixed. This paper initiates an exploration of the accuracy and precision of a Robotic Inspection and Repair System (RIRS), which is a novel robotic railway maintenance system integrated with an industrial manipulator (UR10e) with 6 degree-of-freedom, mounting on an Unmanned Ground Vehicle (UGV) (Warthog) and specially designed trolley. In this research, a mimic track visual inspection test using QR code detection is adopted and implemented by an arm-mounted monocular camera. Then a sequential pose moves with multiple payload weights on the manipulator end has been performed as a performance measurement of repair jobs using a vision-based position tracking algorithm. The measurement results demonstrate that RIRS can maintain accurate and consistent performance in both defect position inspection and repair moves with diverse payloads. For inspection the positional error was only 0.27% while for repair moves the end-effector can reach the same position within 1mm. This research establishes a foundation for system command & control development and supporting more practical railway jobs deployment towards full autonomy for RIRS in the future.
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    Localisation and navigation framework for autonomous railway robotic inspection and repair system
    (SSRN, 2021-10-20) Rahimi, Masoumeh; Liu, Haochen; Rahman, Miftahur; Ruiz Carcel, Cristobal; Durazo-Cardenas, Isidro; Starr, Andrew; Hall, Amanda; Anderson, Robert
    In the path towards the intelligent industrial 4.0, the railway industry is keen to develop intelligent asset management strategies for digitalization and smart management for rail infrastructure. It aims to both reduce the cost and exposure of human-labor, associated with track maintenance risk, as well as increase the autonomy and accuracy for the railway inspection and repair job. A Robotic Inspection and Repair System (RIRS) is proposed to undertake the automated railway maintenance consisting of the autonomous off-track travel between base workshop and track, road-rail conversion, autonomous on-track inspection, and repair as well as remote communicating to railway signaling system and infrastructure system. This paper presents a localization and navigation framework for this new autonomous system; applied to the mentioned railway maintenance job. This system comprises a commercial Unmanned Ground Vehicle (UGV, named Warthog) with a robotic manipulator (UR10e), and multiple onboard sensors including Lidar, camera, RTK GNSS, IMU, wheel odometry, and multiple types of cameras. An adaptive trolley is also designed for the purpose of road-rail conversion. This research also focuses on how to increase accuracy for the support of track defect detection and localization.
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    A practical demonstration of autonomous ultrasonic testing for rail flaws inspection
    (Cranfield University, 2022-11-08) He, Feiyang; Durazo-Cardenas, Isidro; Liu, Haochen; Rahman, Miftahur; Rahimi, Masoumeh; Starr, Andrew; Poulter, Michael
    This study established the viability of autonomous ultrasonic inspections at the technology readiness level 5 (TRL 5). An autonomous ultrasonic rail inspection prototype was developed using commercially available ultrasonic instruments and an unmanned on-track vehicle platform consisting of a Clearpath's Warthog and a road-rail vehicle (RRV) trolley. The prototype was designed to travel back and forth on a segment of the test track during the test programme. Repeated fault checks were able to discover seeded artificial flaws at depths of 23 and 27 mm. The detection was indicated by an audio alarm triggered when the ultrasonic emissions exceeded the threshold of the detector gate. A plain text message sent over local area network (LAN) WIFI to a virtual server was also used to demonstrate the transmission of detection messages. The repeatability of the inspection prototype's positioning relative to the problem was confirmed using odometry, global navigation satellite system (GNSS), and positional measurements. The results of the three measurement methods were in good agreement, and the positioning inaccuracy varied between 3 and 7 cm. This study demonstrated the potential of autonomous ultrasonic checks and gave recommendations for further work and limitations.
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    A review on technologies for localisation and navigation in autonomous railway maintenance systems
    (MDPI, 2022-05-31) Rahimi, Masoumeh; Liu, Haochen; Durazo-Cardenas, Isidro; Starr, Andrew; Hall, Amanda; Anderson, Robert
    Smart maintenance is essential to achieving a safe and reliable railway, but traditional maintenance deployment is costly and heavily human-involved. Ineffective job execution or failure in preventive maintenance can lead to railway service disruption and unsafe operations. The deployment of robotic and autonomous systems was proposed to conduct these maintenance tasks with higher accuracy and reliability. In order for these systems to be capable of detecting rail flaws along millions of mileages they must register their location with higher accuracy. A prerequisite of an autonomous vehicle is its possessing a high degree of accuracy in terms of its positional awareness. This paper first reviews the importance and demands of preventive maintenance in railway networks and the related techniques. Furthermore, this paper investigates the strategies, techniques, architecture, and references used by different systems to resolve the location along the railway network. Additionally, this paper discusses the advantages and applicability of on-board-based and infrastructure-based sensing, respectively. Finally, this paper analyses the uncertainties which contribute to a vehicle’s position error and influence on positioning accuracy and reliability with corresponding technique solutions. This study therefore provides an overall direction for the development of further autonomous track-based system designs and methods to deal with the challenges faced in the railway network.