Quaternion kinematics for the error-state Kalman filter
By Joan Solà. arXiv.org, 2015
633 citations recorded by the source corpus.
A tutorial of quaternion algebra, especially suited for the error-state Kalman filter, with the aim of building Visual-Inertial SLAM and odometry systems.
Subfields: Aerospace Engineering, Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/12412090e46d1b21eecc59d1326edb8e47e9640e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Ryan M. Eustice
- Maani Ghaffari Jadidi
- Ross Hartley
- Jessy W. Grizzle
- Ming Liu
- Haoyang Ye
- Christian E. Pranata
- Chao Qin
In Artificial Intelligence
- Maani Ghaffari Jadidi
- Ross Hartley
- Jessy W. Grizzle
- Ryan M. Eustice
- Christian E. Pranata
- Ming Liu
- Chao Qin
- Shuyang Zhang
Citations in the corpus
- Contact-aided invariant extended Kalman filtering for robot state estimation (2019, methodology): “As the name implies, the error-state extended Kalman filter (ErEKF) is formulated using the errors, such as pose and velocity errors, as the filter variables, whereas the standard EKF tracks the states themselves (pose and velocity directly) (Madyastha et al., 2011; Roumeliotis et al., 1999; Sola, 2”
- PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features (2018, background): “where [q]L and [q]R are the left- and right- quaternion-product matrices, respectively [36].”
- LINS: A Lidar-Inertial State Estimator for Robust and Efficient Navigation (2019, methodology): “Besides, we adopted an error-state representation to guarantee linearization validity [27].”
- A micro Lie theory for state estimation in robotics (2018, background): “Quaternions (please consult [8] for an in-depth reference) may be represented by either of these equivalent forms, q = w + ix+ jy + kz = w + v ∈ H”