Imaging sonar-aided navigation for autonomous underwater harbor surveillance

Abstract

In this paper we address the problem of driftfree navigation for underwater vehicles performing harbor surveillance and ship hull inspection. Maintaining accurate localization for the duration of a mission is important for a variety of tasks, such as planning the vehicle trajectory and ensuring coverage of the area to be inspected. Our approach only uses onboard sensors in a simultaneous localization and mapping setting and removes the need for any external infrastructure like acoustic beacons. We extract dense features from a forwardlooking imaging sonar and apply pair-wise registration between sonar frames. The registrations are combined with onboard velocity, attitude and acceleration sensors to obtain an improved estimate of the vehicle trajectory. We show results from several experiments that demonstrate drift-free navigation in various underwater environments.

Attitude-Trajectory Estimation for Forward-Looking Multibeam Sonar Based on Acoustic Image Registration

“…While there are many technologies to assist in navigation for land or air based vehicles, these technologies do not necessarily transfer well to the underwater environment. Global Positioning System (GPS) may be referenced using underwater acoustic beacons [1], however a system may not always be available, or the accuracy good enough, for tasks such as exploration [2] or underwater inspection [3] [4]. Although inertial navigation systems are unaffected by being underwater, they are costly and subject to drift [5].…”

“…However, underwater optical systems may suffer from poor visibility [9]. A practical alternative is acoustic imaging which being based on acoustic waves is less susceptible to propagation attenuation [3][10] [11]. The use of acoustic waves also allows accurate estimation of the range to an object, though the angle estimation is typically more ambiguous than in optical systems.…”

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

“…Solutions to this problem use either spectral methods [4,5], or feature-based methods [6]. In either case, these techniques have several applications, such as underwater simultaneous localization and mapping (SLAM) [7,8] and photomosaicing [9,10]. However, previous work produces strictly 2D mosaics or 3-degree of freedom (DOF) motion estimates (relative x, y, and heading).…”

Simultaneous Localization and Mapping in Marine Environments

“…8.2.2 to combine onboard navigation information with sonar registration based on automated dense feature extraction [34]. We focus on imaged areas that are locally flat, such as the open areas of ship hulls and the seafloor.…”

“…• Smoothing as an alternative to filtering: the use of nontraditional acoustic range measurements to improve AUV navigation [18] • Relocalizing in an existing map: localizing and controlling an AUV using natural features using a forward looking sonar [23] • Loop closure used to bound error and uncertainty: combining AUV motion estimates with observations of features on a ship's hull to produce accurate hull reconstructions [34] A common theme for all three applications is the use of pose graph representations and associated estimation algorithms that exploit the graphical model structure of the underlying problem. First we will overview the evolution of the SLAM problem in the following section.…”