This paper presents a project on the design of an autonomous robotic crawler, which will be utilized in the inspection of gusset plates in the structures of steel bridges, where conventional methods of entering the site manually will be challenged by future design. Gusset plates that are important in the stability of the bridges should undergo frequent checks to prevent the disastrous failure, which occurred in the I-35W Mississippi River Bridge. Manual inspection poses a threat to life, wastes time, and is prone to errors by individuals; therefore, an alternative to this method is in order. This robotic crawler can be applied to reach the hard-to-reach places with the non-destructive evaluation (NDE) sensors, such as the ultrasonic transducers, visual cameras, and eddy-current probes, targeting the detection of surface and subsurface damages in an autonomous way. This system is used in semi-autonomous and full-autonomous state and gives the inspector immediate, repeatable and high-quality data. The design of the crawler is good as it includes sophisticated navigation algorithms that make it efficient even in harsh conditions. The study shows that this technology has the potential to enhance safety and reduce operational expenses, and improve traditional methods. By resorting to open-access repositories with raw data and sensor data, clearly outlined software and hardware interfaces, and guides for experiment reproduction, the work will enable the replication of results and facilitate further improvements in the field. The self-guided robotic crawler is a radical improvement in the physical maintenance of bridges, and it serves as a sustainable, scalable solution in monitoring the health of infrastructures.

Autonomous Robotic Crawlers, Gusset Plate Inspections, Non-Destructive Evaluation (NDE), Sensor Integration, Data Availability & Reproducibility

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