Monocular visual odometry (VO) is an important task in robotics and computer vision. Thus far, how to build accurate robust monocular VO systems that can work well diverse scenarios remains largely unsolved. In this article, we propose a framework exploit depth estimation for improving VO. The core of our module with strong generalization capability scenes. It consists two separate working mode...

This review is based on a manuscript of 67 pages corresponding to the Master’s thesis of Jan Vakula. The work of this thesis was performed in the Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, under the supervision of Dr. Tomáš Svoboda. The goal of this thesis was to test and improve a visual odometry algorithm developed by Jiri Divis in his ...

Yatima is a mobile robot on a Segway RMP base. This paper describes a method for autonomous navigation of a known map. The laboratory space Yatima is stored in is used as the navigation environment. A map is created, and the ROS navigation stack is used to implement autonomous navigation. Yatima can effectively navigate open areas, but struggles with obstacle avoidance. Simultaneous Localizatio...

Random Sample Consensus (RANSAC) has become one of the most successful techniques for robust estimation from a data set that may contain outliers. It works by constructing model hypotheses from random minimal data subsets and evaluating their validity from the support of the whole data. In this paper we present a novel combination of RANSAC plus Extended Kalman Filter (EKF) that uses the availa...

This paper demonstrates a proof of concept for a platform independent vision based localisation system that can be mounted on any mobile platform and operates in real-time. The system is able to globally localise given a pre-scanned 3D model of the environment. This is a deliberate deviation from the SLAM (Simultaneous Localisation and Mapping) approach because we are interested in global local...

Visual Odometry (VO) is one of the fundamental building blocks of modern autonomous robot navigation and mapping. While most state-of-the-art techniques use geometrical methods for camera ego-motion estimation from optical flow vectors, in the last few years learning approaches have been proposed to solve this problem. These approaches are emerging and there is still much to explore. This work ...

We propose a real-time method for odometry and mapping using range measurements from a 2-axis lidar moving in 6-DOF. The problem is hard because the range measurements are received at different times, and errors in motion estimation can cause mis-registration of the resulting point cloud. To date, coherent 3D maps can be built by off-line batch methods, often using loop closure to correct for d...

In multi-robot simultaneous localization and mapping (SLAM) systems, the system must create a consistent global map with multiple local maps loop closures between robot poses. However, false-positive caused by perceptual aliasing can severely distort map, especially in GNSS-denied areas, where good prior of relative poses robots is unavailable. addition, performance consistency metric existing ...