This article presents a survey of simultaneous localization and map** (SLAM) and data
fusion techniques for object detection and environmental scene perception in unmanned …

Visual-inertial odometry (VIO) is the problem of estimating a robot's trajectory by combining
information from an inertial measurement unit (IMU) and a camera and is of great interest to …

The kinematics of many systems encountered in robotics, mechatronics, and avionics are
naturally posed on homogeneous spaces; ie, their state lies in a smooth manifold equipped …

Stochastic filters for on-line state estimation are a core technology for autonomous systems.
The performance of such filters is one of the key limiting factors to a system's capability. Both …

This work provides a finite-time stable disturbance observer design for the discretized
dynamics of an unmanned vehicle in three-dimensional translational and rotational motion …

This letter re-visits the problem of visual-inertial navigation system (VINS) and presents a
novel filter design we dub the multi state constraint equivariant filter (MSC EqF, in analogy to …

A set of particle filters on matrix Lie groups is presented for state estimation, where the
particles live in Lie algebra. The dynamical equations in the Lie algebraic form and the log …

This paper introduces a new parameterization for the problem of visual inertial simultaneous
localization and map** (VI-SLAM), ie for a robot only equipped with a single monocular …