1 research outputs found
Robust Inertial-aided Underwater Localization and Navigation based on Imaging Sonar Keyframes
Imaging sonars have shown better flexibility than optical cameras in
underwater localization and navigation for autonomous underwater vehicles
(AUVs). However, the sparsity of underwater acoustic features and the loss of
elevation angle in sonar frames have imposed degeneracy cases, namely
under-constrained or unobservable cases according to optimization-based or
EKF-based simultaneous localization and mapping (SLAM). In these cases, the
relative ambiguous sensor poses and landmarks cannot be triangulated. To handle
this, this paper proposes a robust imaging sonar SLAM approach based on sonar
keyframes (KFs) and an elastic sliding window. The degeneracy cases are further
analyzed and the triangulation property of 2D landmarks in arbitrary motion has
been proved. These degeneracy cases are discriminated and the sonar KFs are
selected via saliency criteria to extract and save the informative constraints
from previous sonar measurements. Incorporating the inertial measurements, an
elastic sliding windowed back-end optimization is proposed to mostly utilize
the past salient sonar frames and also restrain the optimization scale.
Comparative experiments validate the effectiveness of the proposed method and
its robustness to outliers from the wrong data association, even without loop
closure.Comment: 11 pages, 12 figures, submitted to journa