Spatial information acquisition and its use for infrastructure operation and maintenance

Site modeling can be useful in various safety-enhancement applications and for as-built data acquisition. For example, simulation-based on-site modeling may assist an equipment operator to avoid incidents that result in human injury or death (or damage to equipment and materials) on construction sites. Also, site modeling is required for realtime applications such as equipment control and as-built data acquisition. Site-modeling methods that are currently in use, including 3D CAD and dense 3D scanning systems, have certain limitations, in that they are time consuming and labor intensive and require high performance computers. This dissertation presents a rapid, on-site, spatial-modeling method using a “sparse point cloud” approach that represents construction sites in an efficient manner. The various procedures used in the modeling process, including a convex-hull algorithm, workspace partitioning, and an algorithm that merges model subsets from different locations to generate construction-site scenes, were developed. Experiments have been conducted to verify the accuracy and speed of the system, as well as its applicability to the representation of actual construction sites. The results of the experiments performed on actual construction sites were presented; as are case studies of the modeling method per se. Experiments of the applications of the proposed sitemodeling method to the simulation of obstacle avoidance in the operation of equipment on an industrial construction project were conducted. The experimental results indicated that the proposed spatial-modeling approach has potential for effective use in a broad class of applications in the construction industry.