CHCNAV’s Apache USV, made of macromolecule polyester carbon fiber and Kevlar fiber-glass, can be carried by a single person. (Image: CHCNAV)

Bridges are essential components of our transportation infrastructure, facilitating seamless travel and connecting communities. The construction and maintenance of a bridge is an ongoing process, influenced by a variety of natural factors, including topography, geology, meteorology and hydrology. To protect the foundations and ensure the structural integrity of bridges, it is critical to continuously monitor bridge piers with a focus on providing consistent data support. For this project, the acquisition of 3D point cloud data of the riverbed surrounding a bridge is essential for the long-term safety monitoring of its abutments.

The Challenge of Traditional Surveying Method

Traditionally, bridge pier surveys are conducted using manned boats equipped with multibeam sonar — a method that, while mature, faces several challenges:

1. Significant safety hazards. Survey areas are prone to tidal changes, high winds, waves, and traffic from passing vessels, which can often create dangerous working conditions. Stone ridges along the riverbanks, potentially hidden during high tide, pose additional risks to manned boats surveying near bridge piers.

2. Low operational efficiency. After a typhoon, the timeline for surveying is tight. However, setting up and calibrating multibeam sonar equipment on manned boats is time-consuming. Operations in shallow areas, such as riverbanks and near central river sandbars, are limited to short periods of low tide, requiring strict adherence to schedules.

3. Poor data quality. Multibeam surveying requires overlaps of more than 20%. Accurate route keeping by manned boats, critical to multibeam surveying, is often compromised by environmental conditions and operator experience, resulting in poor data quality. In addition, GNSS signal reception under bridges is poor, affecting positioning accuracy and thus the integrity and efficiency of data collection.

4. High operational costs. The lack of specialized underwater topographic survey vessels requires the rental of traditional manned boats, which increases project costs.

A USV can operate where it would be dangerous or inefficient for a manned boat. (Image: CHCNAV)

The CHCNAV Solution: Efficient Autonomous Surveying

To overcome these obstacles, one bridge project team implemented an innovative solution: the use of the Apache 6 unmanned surface vessel (USV) coupled with a NORBIT multibeam echosounder and an iLiDAR 3D laser scanner. This integration results in a system that is not only lightweight, compact, and easy to install and operate, but also portable and energy efficient.

The Apache 6 USV, with its all-carbon fiber hull weighing only 15 kg, combines lightness with durability. Its modular design simplifies logistics and transportation, while its ability to withstand offshore conditions and automatically follow pre-determined routes enhances operational efficiency. The system synchronizes surface and underwater data, with beams capable of scanning shallow flats and channel slopes. The echosounder and iLiDAR share position, heading and attitude data to optimize cost efficiency.

The iLiDAR 3D laser scanner features an ultra-lightweight design, with the main unit weighing less than 3 kg. Its high level of integration, requiring only a single cable for full-surface data access, and compatibility with leading multi-beam data acquisition and processing software underscore its utility.

Advantages of Using USVs

Compared to traditional manned boat surveys, the Apache 6 USV’s integration of surface and underwater sensors offers several advantages, including high integration, compact size, safe unmanned operation and lower operating costs. In addition to ensuring the safety of personnel and bridge structures, it increases survey efficiency in complex environments. Using this autonomous survey system, two project engineers were able to create a high-resolution 3D point cloud model of the riverbed scour around the bridge piers at a low operational cost. This dataset is invaluable for ongoing safety monitoring of the bridge piers, facilitating proactive maintenance and ensuring the long-term stability and reliability of this critical transportation infrastructure.