Enhancing Sustainable Maintenance Operations Through Intelligent Climbing Robots

This paper investigates strategies for enhancing the operational effectiveness of climbing robots in performing maintenance tasks in hard-to-reach environments, with a particular emphasis on historical infrastructures like bridges and tunnels. We focus on optimizing the Wall-pushing Autonomous Maintenance Robot (WAuMBot) to rectify issues associated with mechanical sag. Accurate sag compensation is vital for ensuring precise robot localization and motion, especially in challenging spatial contexts such as the steel arches of the Sydney Harbour Bridge. Our research presents a novel methodology that employs sensor fusion and closed -loop control mechanisms for accurate sag error correction. This optimization significantly refines WAuMBot's odometric accuracy, facilitating advanced multi-step planning without necessitating re-Iocalization steps. The augmented capabilities of climbing robots, demonstrated by WAuMBot's enhanced sag correction performance, contribute to the objectives of sustainable maintenance by curtailing deterioration, reducing environmental and social consequences, and offering greater energy and resource efficiency compared to traditional human-operated methods. Moreover, the utility of these robots in high-risk environ-ments substantially increases workplace safety, worker well-being, and overall operational sustainability. The efficacy and viability of the proposed approach have been confirmed through empirical experiments, indicating its promising applications in the maintenance of bridges and analogous infrastructures.