Autonomous Inspection and Data Fusion for Maritime Critical Infrastructures

Abstract

Automation and robotics are essential for the effective monitoring and inspection of maritime critical infrastructures and marine environments. We demonstrate the use of an unmanned surface vehicle, integrated with acoustic and optical sensors, to perform fast and accurate inspections of maritime infrastructures in confined areas (i.e., presence of buildings and multiple obstacles). High resolution maps are obtained fusing offline data from LiDAR and 2D acoustic multi-beam forward looking camera point clouds. The technological pipeline is demonstrated through a survey in Copenhagen harbour. The data acquisition leverages on methods to improve path planning and localization to correct failures in the RTK GNSS due to shadowing of buildings and other obstacles. The entire data flow is streamlined to produce fast delivery time and data access, optimizing data acquisition and processing, providing results into a dedicated web service tailored to users’ needs for knowledge and information extraction.