Automated robots have been deeply embedded in many industries for decades. Autonomous railway maintenance is attracting more attention, but few robotic technologies are used in rolling stock inspection and repair. Due to geometrical differences between rail and road, wheeled robots still need to fulfill research and deployment gaps for application in railway track maintenance. This research is intended to design an autonomous Robotic Inspection and Repair System (RIRS) for unmanned track maintenance. It mainly employs commercial Warthog Unmanned Ground Vehicle (UGV), Universal Robot (e.g., UR10e) manipulator, and multiple onboard sensors to achieve navigation to track, road-rail conversion, and on-track inspection and repair. With the support of a trolley, RIRS will achieve the ability to operate both on-track and off-track. This research also investigates the system structure of the on-track inspection and repair by considering the dynamic degree-of-freedom of both UGV wheels and the joints of robot manipulator. The redundancy of joints for the mobile manipulator has been reduced by proposing simplified joints which will improve the performance and efficiency. This research analyses the dynamic principles of a new maintenance system that will be deployed and tested in a prototype RIRS system in future work.
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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