The ability of intelligent unmanned platforms to achieve autonomous navigation and
positioning in a large-scale environment has become increasingly demanding, in which …

We review the use of factor graphs for the modeling and solving of large-scale inference
problems in robotics. Factor graphs are a family of probabilistic graphical models, other …

Humans are able to form a complex mental model of the environment they move in. This
mental model captures geometric and semantic aspects of the scene, describes the …

We provide an open-source C++ library for real-time metric-semantic visual-inertial
Simultaneous Localization And Mapping (SLAM). The library goes beyond existing visual …

One camera and one low-cost inertial measurement unit (IMU) form a monocular visual-
inertial system (VINS), which is the minimum sensor suite (in size, weight, and power) for the …

Abstract We propose Deep Patch Visual Odometry (DPVO), a new deep learning system for
monocular Visual Odometry (VO). DPVO uses a novel recurrent network architecture …

As inertial and visual sensors are becoming ubiquitous, visual-inertial navigation systems
(VINS) have prevailed in a wide range of applications from mobile augmented reality to …

In recent years there have been excellent results in visual-inertial odometry techniques,
which aim to compute the incremental motion of the sensor with high accuracy and …

In recent years, vision-aided inertial odometry for state estimation has matured significantly.
However, we still encounter challenges in terms of improving the computational efficiency …

We present LINS, a lightweight lidar-inertial state estimator, for real-time ego-motion
estimation. The proposed method enables robust and efficient navigation for ground …