The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a self-memory prediction model to mitigate the effects of image based visual servoing (IBVS) system under uncertainty. The performance of IBVS system is easily influenced by different tasks, diverse environments and uncertain disturbances. Through building a self-memory prediction model to keep previous movement tendency in the every current movement, the framework of a self-memory...
Despite the availability in the literature of several constraint-based motion generation algorithms, modest attention has been paid to their robustness with respect to noise, and more in general, to unstructured uncertainties. Especially in the case of sensor-related constraints, the envisaged robustness properties are clearly crucial to enforce the correct and expected behaviour of these algorithms...
This article addresses the problem of near real time video analysis of a maritime scene using a (moving) airborne RGB video camera in the goal of detecting and eventually recognizing a target maritime vessel. This is a very challenging problem mainly due to the high level of uncertainty of a maritime scene including a dynamic and noisy background, camera's and target's motions, and broad variability...
This paper presents an analysis of the role of measurements uncertainty in the feature-based RGB-D SLAM formulated as graph optimization problem. The considered SLAM solution uses global graph optimization to find the trajectory of the RGB-D camera and a set of 3D point features constituting the map. In order to focus on the optimization back-end details and isolate the results from the data association...
Visual servoing techniques are proven to be beneficial in unstructured workspaces. However, visual servoing is bounded by several constraints and is prone to the uncertainties of the system, leaving it of limited applicability. Several previous works have tackled these problems; yet, most of these works considered only a partial set of the aforementioned shortcomings. This work proposes a novel two-stage...
Visual servoing methods have proven their usefulness for robot control in unstructured environments. However, the practicality of such methods highly depends on their robustness to system uncertainties and ability to handle the constraints of the system. Many of the previous works proposed effective remedies for constraint handling; yet, only a few of them considered the system uncertainties. This...
An RGB-D camera is a sensor which outputs color and depth and information about the scene it observes. In this paper, we present a real-time visual odometry and mapping system for RGB-D cameras. The system runs at frequencies of 30Hz and higher in a single thread on a desktop CPU with no GPU acceleration required. We recover the unconstrained 6-DoF trajectory of a moving camera by aligning sparse...
An urban operation of unmanned aerial vehicles (UAVs) demands a high level of autonomy for tasks presented in a cluttered environment. While fixed-wing UAVs have been well suited for long-endurance missions at a high altitude, their navigation inside an urban area brings more challenges in motion planning and control. The inability to hover and low agility in motion cause more difficulties on planning...
Multiple UAVs can be used to cover a region effectively. Area coverage involves two stages - area decomposition into cells and path planning inside the cells. The area is decomposed using sweeping technique. For path planning inside the cells, a novel method is developed where optimal number of lanes are generated to minimize the number of UAV turns to accomplish the mission in minimum time. Also...
In this paper we present a system for indoor people tracking based on the combination of wearable sensors and a video analysis module. The sensor consists of an inertial platform, which provides attitude and acceleration data with a high rate. Data is fused by an Extended Kaiman Filtering (EKF) to reconstruct the attitude and the accelerations experienced by the wearable sensors. The information is...
In this paper, we present a cooperative approach to geo-localize a ground target using bearing-only localization of Unmanned Aerial Vehicles (UAVs). We design a distributed path planning algorithm using receding horizon control, which improves the localization accuracy of the target and of all of the air vehicles simultaneously while satisfying the observability conditions. We show that the cooperative...
We present a stereo vision-aided inertial navigation system and demonstrate its potential in power line inspection at close range using an unmaned aerial vehicle. This is made possible by recent developments in visual odometry and a newly proposed algorithm for the loose coupling of an inertial measurement unit and visual odometry. Our experiments show promising results.
Vision based simultaneous localization and mapping (SLAM) has recently received much research interest. However, vision based SLAM could be corrupted with the inclusion of moving entities, which makes it hard to operate in dynamic environments. Simultaneous localization, mapping and moving object tracking (SLAMMOT) serves as a solution to deal with moving objects while performing SLAM. The existing...
We present a procedure for egomotion estimation from visual input of a stereo pair of video cameras. The 3D egomotion problem, which has six degrees of freedom in general, is simplified to four dimensions and further decomposed to two two-dimensional subproblems. The decomposition allows us to use a voting strategy to identify the most probable solution, avoiding the random sampling (RANSAC) or other...
Sequential monocular SLAM systems perform drift free tracking of the pose of a camera relative to a jointly estimated map of landmarks. To allow real-time operation in moderately sized environments, the map is kept quite spare with usually only tens of landmarks visible in each frame. In contrast, visual odometry techniques track hundreds of visual features per frame. This leads to a very accurate...
To be able to determine the position of a static object in 3D space by means of computer vision, it has to be seen by cameras from at least two different view points. The same applies for measuring the position of a moving object based on images captured at one single time instant. However, if the cameras are not synchronized in time, or if a moving object is not visible in all images, one can not...
Autonomous and safe robot navigation requires the capability to simultaneously building a map of the environment and a selflocalization of the robot itself. This is known as the SLAM (Simultaneous Localization and Mapping) problem. In such a context, omnidirectional camera looks like a very interesting sensor since it allows a full 360 degrees field of vision. Complexity of the SLAM methods dramatically...
Inverse-depth parameterization can successfully deal with the feature initialization problem in monocular simultaneous localization and mapping applications. However, it is redundant, and when multiple landmarks are initialized from the same image, it fails to enforce the ldquocommon originrdquo constraint. The authors propose two new variants that addresses both of these issues. The experimental...
Path-planning allows one to steer a camera to a desired location while taking into account the presence of constraints such as visibility, workspace, and joint limits. Unfortunately, the planned path can be significantly different from the real path due to the presence of uncertainty on the available data, with the consequence that some constraints may be not fulfilled by the real path even if they...
This paper discusses an approach to using the Cramer Rao Lower Bound (CRLB) as a trajectory design tool for autonomous underwater vehicle (AUV) visual navigation. We begin with a discussion of Fisher Information as a measure of the lower bound of uncertainty in a simultaneous localization and mapping (SLAM) pose-graph. Treating the AUV trajectory as an non-random parameter, the Fisher information...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.