An automated system for scanning and characterizing unbound aggregates, called the 'Laser-based Aggregate Scanning System'(LASS), has been developed at the University of Texas at Austin. The system uses a laser profiler to acquire and analyze true three-dimensional data on aggregate particles to measure various morphological properties. Tests have demonstrated that the system can rapidly and accurately measure grain size distribution and dimensional ratios, and can objectively quantify particle shape, angularity, and texture in a size invariant manner. In its present state of development, the LASS machine is a first-generation, laboratory testing device. With additional development, this technology is expected to provide high-quality, detailed information for laboratory and on-line quality control during aggregate production.

Unstructured workspaces which are typical in construction contain unpredicable activities as well as changing environments. Most automated and semi-automated construction tasks require real-time information about the local workspace in the form of 3D geometric models. This paper describes and demonstrates a new rapid, local area geometric data extraction and 3D visualization method for unstructured construction workspaces that combines human perception, simple sensors, and descriptive CAD models. The rapid approach will be useful in construction in construction in order to optimize automated equipment tasks and to significantly improve safety and a remote operator's spatial perception of the workspace.