RESUMO
In this paper, a portable three-dimensional (3D) scanning system for the accurate characterization of large raw material (e.g., cereal grain, coal, etc.) stockpiles is presented. The system comprises an array of high resolution millimeter-wave radars and a cm-level accuracy positioning system to accurately characterize large stockpiles by means of a high-resolution 3D map, making it suitable for automation purposes. A control unit manages the data received by the sensors, which are sent to a computer system for processing. As a proof of concept, the entire sensor system is evaluated in a real environment for electromagnetically scan a scaled stockpile of coal, used in the industry for handling raw materials. In addition, a highly efficient processing adaptive algorithm that may reconstruct the scanned structure in real-time has been introduced, enabling continuous dynamic updating of the information. Results are compared with those from a photogrammetry-like technique, revealing an excellent agreement.
RESUMO
Millimetre-wave imaging is a powerful non-destructive inspection technique which has become widely used in areas such as through-the-wall imaging or concealed weapon detection. Nevertheless, current systems are usually limited to either a single view point providing a limited 3D millimeter-wave model or a multiview relying on the accurate movement of a robot arm through precise positions resulting in very bulky systems. In this paper, we present a set of techniques to achieve a multiview millimetre-wave scanner. The aperture of the scanner is kept below 16 cm so it can be portable and, consequently, multiview can be achieved by simple hand movements. In addition, optical images are also acquired with a two-fold purpose: i) building a complementary 3D-model by employing Structure from Movement (SfM) techniques; ii) estimating the scanner position and poses. The proposed technology is illustrated for people screening, proving the capacity of the system to detect hidden weapons.