Mobile phone based laser scanning as a low-cost alternative for multidisciplinary data collection

Abstract

Airborne and terrestrial laser scanners have traditionally been used as specialised toolsets for three-dimensional scene capture in engineering, providing highly accurate measurements with increasingly minimal human interaction. However, commercial or engineering-grade scanning instruments remain expensive and sensitive, requiring costly routine calibrations to ensure their optimum functionality. The recent inclusion of laser scanning sensors by mobile phone corporations such as Apple Computer Inc. is now analogous to the integration of Global Navigation Satellite Systems (GNSS) and cameras into smartphones as seen decades ago. Likely, these initial efforts to include the scanning sensor in mobile phones will see rapid improvements in the application and accuracy of the sensor to serve the growing need for scanning applications for transdisciplinary users. However, there is a limited amount of literature that benchmarks the emerging and low-cost scanning sensors to existing commercial ones to inform practice, thus prompting a need for researchers to evaluate and provide scientific evidence that can inform multidisciplinary scanning. It was noted that there was some absolute positional shift and scan drift in the iPhone Light Detection and Ranging (LiDAR) data. The researchers therefore investigated the extent to which the accuracy of laser scanning tools available within the iPhone 12 Pro compared to engineering-grade laser scanners. Outcomes from the study showed that iPhone scanners can deliver the required models, despite being unstable in dynamic environments when pitched against engineering-grade LiDAR scanners. The research recommends that stabilisers, such as stabilising gimbals or enhanced GNSS receivers, be used in practice to achieve improved accuracy from the mobile phone LiDAR.
Significance:
Laser scanners offer multiple advantages for modelling features in three dimensions in diverse applications, including documentation, archaeology, environmental modelling and mapping. However, the cost of entry to acquire scan data has been a limitation to its wide-scale use across multiple disciplines. This study demonstrated from an accuracy-based perspective that iPhone scanners can deliver the required models addressing different model purposes, despite being slightly unstable when pitched against engineering-grade Light Detection and Ranging (LiDAR) scanners. The results are significant in reinforcing the competence of low-cost tools in increasing access and use of this technology in curating three-dimensional models for multidisciplinary work.