Improving MMS Performance during Infrastructure Surveys through Geometry Aided Design
Received: 2 October 2016 / Revised: 28 November 2016 / Accepted: 29 November 2016 / Published: 8 December 2016
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A Mobile Mapping System (MMS) equipped with laser scanners can collect large volumes of LiDAR data in a short time frame and generate complex 3D models of infrastructure. The performance of the automated algorithms that are developed to extract the infrastructure elements from
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A Mobile Mapping System (MMS) equipped with laser scanners can collect large volumes of LiDAR data in a short time frame and generate complex 3D models of infrastructure. The performance of the automated algorithms that are developed to extract the infrastructure elements from the point clouds and create these models are largely dependent on the number of pulses striking infrastructure in these clouds. Mobile Mapping Systems have evolved accordingly, adding more and higher specification scanners to achieve the required high point density, however an unanswered question is whether optimising system configuration can achieve similar improvements at no extra cost. This paper presents an approach for improving MMS performance for infrastructure surveys through consideration of scanner orientation, scanner position and scanner operating parameters in a methodology referred to as Geometry Aided Design. A series of tests were designed to measure point cloud characteristics such as point density, point spacing and profile spacing. Three hypothetical MMSs were benchmarked to demonstrate the benefit of Geometry Aided Design for infrastructure surveys. These tests demonstrate that, with the recommended scanner configuration, a MMS, operating one high specification scanner and one low specification scanner, is capable of comparable performance with two high-end systems when benchmarked against a selection of planar, multi-faced and cylindrical targets, resulting in point density improvements in some cases of up to 400%.