Abstract

This study addresses three-dimensional (3D) reconstruction of bridge structures over water by fusing sensor measurements from inertial sensors, cameras and lidars mounted on an unmanned surface vehicle (USV). While the accurate navigation capability is strongly required for successful 3D reconstruction, global positioning system (GPS) signals which are essential for accurate navigation are severely deteriorated near the bridge structures or almost completely blocked underneath the bridge decks. In this study, a parameterized feature map is introduced by augmenting the map state with the geometric parameters of the detected bridge piers, and relative navigation is performed with respect to this map in the framework of simultaneous localization and mapping (SLAM). This parameterized SLAM approach allows for high-precision navigation and mapping with no need of GPS fixes. The feasibility of the proposed algorithm was demonstrated through field experiments.

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