Iterated extended Kalman filter based visual-inertial odometry using direct photometric feedback

By Michael Bloesch, Michael Burri, Sammy Omari, Marco Hutter, Roland Yves Siegwart. Int. J. Robotics Res., 2017

489 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Geology

View Paper: https://www.semanticscholar.org/paper/244f95b180abaae5ade032fbd9539b56e5f422db

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Citations in the corpus

An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments (2019, methodology): “We further use the setup of Section VI and rovio [27] for visual-inertial state estimation.”
Visual-Inertial Navigation: A Concise Review (2019, methodology): “The (right) invariant Kalman filter [56] was recently employed to improve filter consistency [25, 57, 58, 59, 60], as well as the (iterated) EKF that was also used for VINS in robocentric formulations [22, 61, 62, 63].”
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual–Inertial, and Multimap SLAM (2020, methodology): “While these systems rely on features, ROVIO [41], [42] feeds an EFK with photometric error using direct data association.”
LINS: A Lidar-Inertial State Estimator for Robust and Efficient Navigation (2019, methodology): “In iterated Kalman filtering, the state update can be linked to an optimization problem [7], [29] considering the deviation from the prior −xk bk+1 and the residual functions, f (·), (i.”
The TUM VI Benchmark for Evaluating Visual-Inertial Odometry (2018, methodology): “ROVIO is more prone to drift and diverges on several sequences, which might be explained by it’s use of a Kalman filter compared to computationally more demanding non-linear least squares optimization employed by OKVIS, VINS-Mono and BASALT.”
PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features (2018, methodology): “• We compare the performances of the proposed PL-VIO with three state-of-the-art monocular VIO methods including ROVIO [17], OKVIS [18], and VINS-Mono [32] on both the EuRoc dataset and the PennCOSYVIO dataset, for which detailed evaluation results are reported.”