DescriptionRepair procedures are vital to maintain the integrity of long-term structures such as bridges, roads, and space habitats. To reduce the burden of manual inspection and repair of long-term environments, the proposed solution is an autonomous repair system used for damage detection and damage repair with very little human intervention. The primary purpose of this thesis is to lay the groundwork for the introductory steps related to detection of damage and creation of a virtual map for navigation in this system. It covers the process of initial detection of damage on a structure, confirmation of damage with detailed red-green-blue-depth (RGB-D) scanning, and development of a virtual map of the structure for navigation and localization of important features. We begin by reviewing numerous damage detection methods and establishing a case for optical 2D stereo imaging and 3D scanning. We performed image-processing and point cloud-processing methods to isolate damage in image and point cloud data. The potential of automating operation and data processing without human intervention is also discussed. To lay the groundwork of an autonomous system, a robot was set up to navigate in a virtual ROS environment and relay sensory information of its surroundings. This process establishes a framework for navigation and detecting damage in a system.