Computer vision techniques, in conjunction with acquisition through remote cameras and
unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure …

SLAM is an abbreviation for simultaneous localization and mapping, which is a technique for
estimating sensor motion and reconstructing structure in an unknown environment …

We present a novel tightly-coupled LiDAR-inertial odometry and mapping scheme for both
solid-state and mechanical LiDARs. As frontend, a feature-based lightweight LiDAR …

We propose a direct (feature-less) monocular SLAM algorithm which, in contrast to current
state-of-the-art regarding direct methods, allows to build large-scale, consistent maps of the …

Unmanned aerial vehicles (UAVs) have recently rapidly grown to facilitate a wide range of
innovative applications that can fundamentally change the way cyber-physical systems …

We present VI-DSO, a novel approach for visual-inertial odometry, which jointly estimates
camera poses and sparse scene geometry by minimizing photometric and IMU …

The goal of our work is to provide a fast and accurate method to estimate the camera motion
from RGB-D images. Our approach registers two consecutive RGB-D frames directly upon …

We propose a real-time, direct monocular SLAM method for omnidirectional or wide field-of-
view fisheye cameras. Both tracking (direct image alignment) and mapping (pixel-wise …

This paper demonstrates an innovative and simple solution for obstacle detection and
collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with …

We propose a novel direct visual-inertial odometry method for stereo cameras. Camera
pose, velocity and IMU biases are simultaneously estimated by minimizing a combined …