An Adaptive Relational Database Development for Construction Robotic Application
Open Access
- Author:
- Beauchat, Tessa
- Area of Honors:
- Architectural Engineering
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Yuqing Hu, Thesis Supervisor
Richard Mistrick, Thesis Honors Advisor - Keywords:
- Construction robotics
robotics
construction
database design
relational database - Abstract:
- The domain of construction robotics has been rapidly advancing in recent years. The rise of this technology has occurred for various reasons, but largely in response to the declining skilled labor making up the construction workforce. Construction robotics provide a reliable way to supplement the workforce, but also provide various other benefits in their implementation. This technology can improve jobsite safety, maximize efficiency, and work in conditions that may not be ideal or possible for human workers. While the technology surrounding construction robotics is rapidly advancing, integration within jobsites is occurring at a significantly slower rate. There are a variety of factors that are affecting adoption of this new technology, but many of them can be attributed to a lack of familiarity and knowledge surrounding construction robotics, which lead individuals to be hesitant regarding their implementation within a jobsite. In order to best utilize this novel technology, it is imperative that advancements and discoveries about how to best integrate construction robotics within jobsites, schedules, and sequencing of work is being holistically researched alongside the technology itself. Capturing information about construction robotics in a usable format is a prerequisite to achieve this. This research aims to develop and validate a relational database model that can capture key features about construction robotics. Developing an accurate and effective way to manage data surrounding construction robotics enables significant future work including, but not limited to allowing individuals to search for robots and their associated information, creating opportunities to integrate robotic data into pre-existing construction robotic tools, and allowing construction teams to make more informed decisions regarding integrating construction robotics on their jobsites.