CHC Navigation (CHCNAV) has released the AU20 MMS, a vehicle-mounted mobile mapping system designed for accurate and efficient collection of 3D spatial data. The system combines high-performance lidar technology, versatile sensor support and intelligent data processing to provide a practical and flexible solution for professionals in road surveying, asset management and infrastructure documentation.

The AU20 MMS features a sophisticated lidar system that uses fourth-generation real-time waveform processing technology. It achieves a scan rate of 2 million points per second and 200 revolutions per second, producing point cloud data with 5 mm accuracy and 3 mm precision. This level of detail allows for the identification of fine surface characteristics and features, supporting comprehensive asset inventories and condition assessments. The system’s long-range, multi-cycle laser technology enables high-density data capture up to 250 m in vehicle-mounted applications.

Built on the adaptable AP7 vehicle platform, the AU20 MMS supports a dual laser scanner setup to increase data density. The platform includes a 45° scanning angle to reduce data shadows and improve detection of vertical structures and road signage. The AP7’s built-in processor allows integration of up to eight external sensors, including specialized pavement detection cameras and panoramic cameras such as the Ladybug5+ and Ladybug6, giving users flexibility in data acquisition strategies.

The AU20 MMS uses artificial intelligence-based algorithms to refine data quality and streamline processing. AI-driven vehicle motion trajectory adjustment automatically identifies control points, correcting point cloud inaccuracies to within two centimeters to meet highway-grade survey requirements. AI-powered panoramic coloring achieves more than 95 percent accuracy in recognizing and handling vehicles and pedestrians, resulting in clean, interference-minimized colorized point clouds with efficient one-click optimization.

CHCNAV’s software suite, CoPre and CoProcess, streamlines workflows through intelligent automation. CoPre optimizes data preprocessing, allowing real-time adjustments to point clouds and imagery while minimizing manual intervention. CoProcess uses AI algorithms for feature extraction, including road assets, terrain models and building structures, to accelerate project delivery.