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Found 9 papers, 6 papers with code
Invariant Smoothing with low process noise
In this paper we address smoothing-that is, optimisation-based-estimation techniques for localisation problems in the case where motion sensors are very accurate.
The Geometry of Navigation Problems
While many works exploiting an existing Lie group structure have been proposed for state estimation, in particular the Invariant Extended Kalman Filter (IEKF), few papers address the construction of a group structure that allows casting a given system into the framework of invariant filtering.
Associating Uncertainty to Extended Poses for on Lie Group IMU Preintegration with Rotating Earth
The recently introduced matrix group SE2(3) provides a 5x5 matrix representation for the orientation, velocity and position of an object in the 3-D space, a triplet we call ''extended pose''.
Robotics
Denoising IMU Gyroscopes with Deep Learning for Open-Loop Attitude Estimation
This paper proposes a learning method for denoising gyroscopes of Inertial Measurement Units (IMUs) using ground truth data, and estimating in real time the orientation (attitude) of a robot in dead reckoning.
Generalized mean shift with triangular kernel profile
In order to situate this new class of methods in the general picture of the Mean Shift theory, we alo give a synthetic exposure of existing results of this field.
AI-IMU Dead-Reckoning
In this paper we propose a novel accurate method for dead-reckoning of wheeled vehicles based only on an Inertial Measurement Unit (IMU).
RINS-W: Robust Inertial Navigation System on Wheels
This paper proposes a real-time approach for long-term inertial navigation based only on an Inertial Measurement Unit (IMU) for self-localizing wheeled robots.
Robotics
An EKF-SLAM algorithm with consistency properties
In this paper we address the inconsistency of the EKF-based SLAM algorithm that stems from non-observability of the origin and orientation of the global reference frame.
Robotics Systems and Control
The invariant extended Kalman filter as a stable observer
We analyze the convergence aspects of the invariant extended Kalman filter (IEKF), when the latter is used as a deterministic non-linear observer on Lie groups, for continuous-time systems with discrete observations.
Systems and Control
