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In this paper we present the development of a multi-rotor system for autonomous outdoor flights in an unknown environment. We propose a modular framework scheme to perform the functions of guidance, navigation and control using the sensor measurements. The localization and mapping tasks are performed simultaneously by the guidance module through an Extended Kalman Filter (EKF). The estimated map allows...
In this paper we present a real-time approach to stitch large-scale aerial images incrementally. A monocular SLAM system is used to estimate camera position and attitude, and meanwhile 3D point cloud map is generated. When GPS information is available, the estimated trajectory is transformed to WGS84 coordinates after time synchronized automatically. Therefore, the output orthoimage retains global...
A potential loop-closure image pair passes the geometric verification test if the number of inliers from the computation of the geometric constraint with RANSAC exceed a pre-defined threshold. The choice of the threshold is critical to the success of identifying the correct loop-closure image pairs. However, the value for this threshold often varies for different datasets and is chosen empirically...
Localization is one of the important topics for autonomous driving of unmanned ground vehicle(UGV). Most problems in localization are due to uncertainties in the modeling and sensors. Therefore, various filters method are developed to estimate the states with noise. Recently, particle filter is widely used because it can be applied to the system with nonlinear model and non-Gaussian noise. In this...
The ability to recognize known places is an essential competence of any intelligent system that operates autonomously over longer periods of time. Approaches that rely on the visual appearance of distinct scenes have recently been developed and applied to large scale SLAM scenarios. FAB-Map is maybe the most successful of these systems. Our paper proposes BRIEF-Gist, a very simplistic appearance-based...
This paper presents a novel approach to navigation in an a priori unknown, GPS-denied environment. The aim is to combine dynamic path planning with the ability to learn about the environment. The vehicle is tasked with autonomous travel from an uncertain initial position to an uncertain target, without prior mapping information. The environment is modelled using linear segments that represent boundaries...
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