Accurate localization of a vehicle is a fundamental challenge and one of the most important
tasks of mobile robots. For autonomous navigation, motion tracking, and obstacle detection …

This paper presents a complete review of computer vision algorithms and vision-based
intelligent applications, that are developed in the field of the Unmanned Aerial Vehicles …

NASA's Perseverance rover uses robotic autonomy to achieve its mission goals on Mars. Its
self-driving autonomous navigation system (AutoNav) has been used to evaluate 88% of the …

Simultaneous localization and map** (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

Direct methods for visual odometry (VO) have gained popularity for their capability to exploit
information from all intensity gradients in the image. However, low computational speed as …

The second ExoMars mission will be launched in 2020 to target an ancient location
interpreted to have strong potential for past habitability and for preserving physical and …

Here, we present a general framework for combining visual odometry and lidar odometry in
a fundamental and first principle method. The method shows improvements in performance …

Visual odometry (VO) is the process of estimating the egomotion of an agent (eg, vehicle,
human, and robot) using only the input of a single or multiple cameras attached to it …

We present a data processing pipeline to online estimate ego‐motion and build a map of the
traversed environment, leveraging data from a 3D laser scanner, a camera, and an inertial …

Part II of the tutorial has summarized the remaining building blocks of the VO pipeline:
specifically, how to detect and match salient and repeatable features across frames and …