Advanced perception, navigation and planning for autonomous in-water ship hull inspection

Abstract

Inspection of ship hulls and marine structures using autonomous underwater vehicles has emerged as a unique and challenging application of robotics. The problem poses rich questions in physical design and operation, perception and navigation, and planning, driven by difficulties arising from the acoustic environment, poor water quality and the highly complex structures to be inspected. In this paper, we develop and apply algorithms for the central navigation and planning problems on ship hulls. These divide into two classes, suitable for the open, forward parts of a typical monohull, and for the complex areas around the shafting, propellers and rudders. On the open hull, we have integrated acoustic and visual mapping processes to achieve closed-loop control relative to features such as weld-lines and biofouling. In the complex area, we implemented new large-scale planning routines so as to achieve full imaging coverage of all the structures, at a high resolution. We demonstrate our approaches in recent operations on naval ships.

Simultaneous Localization and Mapping in Marine Environments

“…The uncorrected coordinates estimated by the vehicle significantly differed after longer operation, showing the effectiveness of our navigation system in eliminating longterm drift. A fuller and more complete overview of this particular project can be found in [32], which also presents more detailed experimental results and demonstrations. In addition to the sonar-based measurements discussed in this section, the wider project also incorporated information extracted from the optical camera illustrated in Fig.…”

High Level Framework for Bridge Inspection Using LiDAR-Equipped UAV

“…Other methods, such as Traveling Salesman Problem (TSP), focus on finding the shortest path passing through pre-defined viewpoints [25,26]. Minimizing the number of viewpoints using Art Gallery Problem (AGP) is another approach to compute the optimal path [27,28,29]. Coverage path planning has been mostly applied on 3D-mapping [30,31], surveying of urban environments [32,33,34], ship hull inspection [28,35,36], and structural inspection [37].…”

“…Minimizing the number of viewpoints using Art Gallery Problem (AGP) is another approach to compute the optimal path [27,28,29]. Coverage path planning has been mostly applied on 3D-mapping [30,31], surveying of urban environments [32,33,34], ship hull inspection [28,35,36], and structural inspection [37]. The model of Bircher et al [37] which is based on Lin-Kernighan Heuristic (LKH) as a TSP solver, convex optimization, and Rapidly-exploring Random Tree star (RRT*) algorithm to define the optimized viewpoints and path, can be applied for other types of structures.…”

Building 3D mosaics from an Autonomous Underwater Vehicle, Doppler velocity log, and 2D imaging sonar

“…We use data collected from the Hovering Autonomous Underwater Vehicle (HAUV) [21,22] to experimentally evaluate our method for creating 3D mosaics. The imaging sonar used on the HAUV is a Sound Metrics Dual frequency IDentification SONar (DIDSON) [23].…”