Original Contributions to the Theory of Autonomous Structural Repair Systems Using Mobile Robotic Platforms for Bridge Infrastructure in the North Central Geopolitical Zone

Bridge infrastructure deterioration in the North Central geopolitical zone of Nigeria, encompassing states including Kwara, Kogi, Niger, and Benue, represents a critical public safety challenge, with a significant proportion of federal road bridges exhibiting advanced structural deficiencies attributed to deferred maintenance. Autonomous robotic systems capable of detecting, assessing, and executing targeted structural repairs offer a transformative solution to the chronic maintenance backlog in an environment where skilled bridge inspection and repair personnel are scarce and access scaffolding deployment is costly. This dissertation makes original contributions to the theory of autonomous structural repair systems using mobile robotic platforms for bridge concrete infrastructure, developing novel formulations for repair task planning, contact force control during concrete surface preparation, and repair material deposition. A hierarchical task representation theory is developed that decomposes a bridge repair mission into inspection, damage characterization, repair sequence planning, and execution sub-problems, with formal specifications expressed in linear temporal logic enabling rigorous verification of task completeness. A model-based force control framework for a grinding end-effector attached to a magnetically adherent climbing robot is derived, incorporating contact mechanics of concrete surfaces and real-time adaptation to surface irregularity. A novel repair material deposition model for autonomous shotcrete application is developed, relating spray nozzle dynamics, material rheology, and target surface geometry to deposit thickness distribution with quantified uncertainty bounds. Field trials of a laboratory prototype climbing robot are conducted on a decommissioned bridge span in Niger State, demonstrating automated damage mapping accuracy of 93 percent and repair layer thickness uniformity within plus or minus 4 millimetres. Keywords: autonomous repair robot, bridge maintenance, climbing robot, structural repair, North Central Nigeria