'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
This paper describes a framework for sensor fusion
of navigation data with camera-based 5 DOF relative pose
measurements for 6 DOF vehicle motion in an unstructured
3D underwater environment. The fundamental goal of this work
is to concurrently sstimate online current vehicle position and
its past trajectory. This goal is framed within the context of
improving mobile robot navigation to support sub-sea science
and exploration. Vehicle trajectory is represented by a history
of poses in an augmented state Kalman filter. Camera spatial
constraints from overlapping imagery provide partial observation
of these posa and are used to enforce consislency and provide a
mechanism for loop-closure. The multi-sensor camera+navigation
framework is shown to have compelling advantages over a
camera-only based approach by 1) improving the robustness of
pairwise image registration, 2) setting the free gauge scale, and
3) allowing for a unconnected camera graph topology. Results
are shown for a real world data set collected by an autonomous
underwater vehicle in an unstructured undersea environment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86055/1/reustice-32.pd
