Dr. Aaron Morris, CEO, Allpoint Systems (USA)
Dr. Aaron Morris, Ph.D. graduate of Carnegie Mellon University (CMU) and founder of Allpoint, was part of an autonomous robot program that mapped underground spaces with 3D LiDAR. The purpose of the program was to collect vast amounts of 3D measurement data and build 3D models of the underground spaces. Shortly into the program, Aaron experienced an unanticipated problem that surveyors and engineers continue to face today: software tools needed to process large volume of files and data generated by a laser scanner did not exist. Allpoint's technology is derived from a fusion of computer vision and mobile robotics research and technology.
Presentation Abstract
Case Study of a Large-Scale, Automated Mobile LiDAR Project (with Michael Frecks, President & CEO, Terrametrix)
The California Department of Transportation (Caltrans) in the US needed to conduct a survey of overhead bridge clearance measurements for the purpose of updating the National Bridge Inventory, overhead clearance signs and routing of permit loads within the state. With over 7,200 overhead bridge spans statewide, Caltrans conducted a pilot project using the StreetMapper mobile mapping system operated by Terrametrix to test the benefits of a mobile mapping system. The state wanted accurate results with little to no disruption to highway traffic. The StreetMapper solution enabled safe, large-scale use of laser mapping by eliminating manual inefficiencies and reducing the chance for error. However, processing 800 miles of high-quality, survey-controlled LiDAR and 600 bridges of varying types presented processing challenges on the back end. Mobile systems are creating a mountain of data that is difficult to process. A week of data collection can take months to process. Terrametrix chose to use Allpoint System’s Perception Engine™ to automatically batch process the directories of 3D data. Allpoint’s system uses a hybrid of software tools that mix automation (for time consuming repetitive tasks) with streamlined user interaction (for efficient high level decision making) to reduce processing time to days or weeks. This presentation will describe the methods, tools and results of the combined use of TMLS survey data collection and innovative automated extraction tools and will discuss the range of other applications and features made possible with an automated processing platform.
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