Abstract
PurposeDigital documentation techniques of tunneling excavations at archaeological sites are becoming more common. These methods, such as photogrammetry and LiDAR (Light Detection and Ranging), are able to create precise three-dimensional models of excavations to complement traditional forms of documentation with millimeter to centimeter accuracy. However, these techniques require either expensive pieces of equipment or a long processing time that can be prohibitive during short field seasons in remote areas. This article aims to determine the effectiveness of various low-cost sensors and real-time algorithms to create digital scans of archaeological excavations.Design/methodology/approachThe authors used a class of algorithms called SLAM (Simultaneous Localization and Mapping) along with depth-sensing cameras. While these algorithms have largely improved over recent years, the accuracy of the results still depends on the scanning conditions. The authors developed a prototype of a scanning device and collected 3D data at a Maya archaeological site and refined the instrument in a system of natural caves. This article presents an analysis of the resulting 3D models to determine the effectiveness of the various sensors and algorithms employed.FindingsWhile not as accurate as commercial LiDAR systems, the prototype presented, employing a time-of-flight depth sensor and using a feature-based SLAM algorithm, is a rapid and effective way to document archaeological contexts at a fraction of the cost.Practical implicationsThe proposed system is easy to deploy, provides real-time results and would be particularly useful in salvage operations as well as in high-risk areas where cultural heritage is threatened.Originality/valueThis article compares many different low-cost scanning solutions for underground excavations, along with presenting a prototype that can be easily replicated for documentation purposes.
Subject
Urban Studies,General Business, Management and Accounting,Geography, Planning and Development,Conservation
Reference41 articles.
1. A method for registration of 3-d shapes;IEEE Transactions on Pattern Analysis and Machine Intelligence,1992
2. Simultaneous localization and mapping: a survey of current trends in autonomous driving;IEEE Transactions on Intelligent Vehicles,2017
3. A comparison of slam algorithms based on a graph of relations,2009
4. Ancient lowland maya complexity as revealed by airborne laser scanning of northern Guatemala;Science,2018
5. The use of lidar in understanding the ancient maya landscape: Caracol and Western Belize;Advances in Archaeological Practice,2014
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