Real-Time Vision Based Auv Navigation System Using a Complementary Sensor Suite

Abstract

This paper proposes a real-time navigation system for an AUV that takes advantage of the complementary performance of a sensor suite including a DVL, a compass, a depth sensor and altimeter sensors with a feature based motion estimator using vision. To allow for real-time performance of the vision based motion estimator a simple but fast correlation algorithm is used for feature matching. The compass and the depth sensors are used to bound the drift of the heading and depth estimations respectively. The altimeter is required in order to translate the feature displacements measured from the images into the metric displacements of the robot. While the robot must rely on DVL navigation above a certain altitude where vision is useless, DVL measurements can be complemented with higher frequency accurate motion estimates from the vision system when navigating close to the seafloor.

A method for estimating the motion of a marine remotely operated vehicle using an underwater vision system

“…The work of the authors in vision based UUV navigation with the addition of a Scale Invariant Feature Transform -SIFT based motion estimation algorithm to improve image correspondence and the use of the latest Graphical Processing Units (GPU) technology in order to perform in real-time is reported in , Horgan et al, 2007.…”

Computer Vision Applications in the Navigation of Unmanned Underwater Vehicles

“…The use of inertial measurements also reduces the amount of visual information required for extraction from the vision system resulting in a more simple and robust solution (Huster et al 2002).While vision based motion estimation techniques rely on the fusion of altitude measurements from sensors to estimate metric displacement (Cufi et al 2002), Eustice ) also takes advantage of other sensor information (attitude) in order to overcome many of the challenging issues involved in visual SLAM based navigation in an unstructured environment. The authors of this chapter, Horgan et al propose a real-time navigation system for a UUV that takes advantage of the complementary performance of a sensor suite including a DVL, a compass, a depth sensor and altimeter sensors with a feature based motion estimator using vision (Horgan et al 2007). The compass and the depth sensors are used to bound the drift of the heading and depth estimations respectively.…”