2G Robotics has recently launched the ULS-200, a mid-range underwater laser scanner. The most versatile of 2G Robotics’ series of ULS systems, the ULS-200 provides many of the benefits of the small, short-range ULS-100, while allowing for the extensive variety of applications provided by the larger, long-range ULS-500. The ULS-200 ideal scan range is between 0.25m and 2.5m. This longer scanning range makes the ULS-200 relevant to a more extensive range of applications.
It retains the compact, lightweight design of the ULS-100 (1.29kg in water). At just 29.2cm in height and 33.2cm long, the ULS-200 is capable of underwater measurements in confined spaces, and as with all ULS scanners, can be easily deployed by a diver. Requiring minimal power (12 VDC to 24 VDC @ 1A maximum) for operation, the ULS-200 also utilizes standard RS-485 and RS-232 connections, making the system easily compatible with almost any ROV/AUV.
These features make the ULS-200 extremely versatile. The system is relevant to a wide range of measurement tasks (in water or air) that require precision and accuracy. As with 2G Robotics’ other models, the ULS-200 employs innovative laser technology and features silt and ambient light filtering functions to produce very highly detailed 3D scans at resolutions hundreds of times higher than that of sonar technology.
Operable to depths of 350m, the ULS-200 emits a line of laser light, which reflects off the target and is captured by the device’s optical sensor. The sensor then triangulates hundreds of points along the laser line, collecting up to one million points per scan, creating a detailed digital 3D model.
Because the system’s laser technology gathers such dense data measurements, the ULS-200 is able to produce extremely precise scans that accurately resolve fine details such as cracks, dents, or other anomalous features pertinent to a structure’s integrity. The ULS-200 therefore redresses significant limitations posed by sonar technology, which proves ineffective in small, echo-prone spaces and creates low resolution models that can lead analysts to make risky, assumption-based decisions.