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Improving the Efficiency of Geometry & Visual Data Collection for Bridges

The Trimble Fund is partially sponsoring a PhD studentship on “Improving the Efficiency of Geometry & Visual Data Collection for Bridges”. The objective of this research is to device a system made of appropriate hardware and software that will be able to collect registered point cloud and image data of appropriate quality for bridge as-is modelling and inspection. A previous Trimble studentship at the department has determined the data quality requirements for as-is modelling (resolution, accuracy, etc.). The new studentship will devise a system that could provide this data in an efficient manner. Such a system does not currently exist and the current state of the art hardware (laser scanners, high res cameras) and registration software are not fit for purpose when the objective is to collect and post-process such a dataset in less than a day. The new system is expected to combine a mini laser scanning sensor of the size of a Velodyne Puck with a high resolution (> 40 MPixels), high frame rate shooting conventional DSLR in a common pre-registered enclosure, and create the software methods needed to progressively build an image-registered 3D dataset that meets the accuracy and resolution standards of bridge principal inspection.

Partial funding of a studentship was requested from and awarded by the Trimble Fund in Michaelmas 2016. Additional funding is being sought to complement Trimble’s generous support. The scope of this studentship is to devise a hybrid portable/mountable system for high resolution, high accuracy surveying. The studentship was advertised in December 2016 and attracted several applicants. It was awarded to applicant Sevde Baltasi, who is expected to start in October 2017. The research activities will begin then. This studentship is expected to be completed in 2021.