A review of sensor fusion techniques for underwater vehicle navigation

This work provides a general description of the multi sensor data fusion concept, along with a new classification of currently used sensor fusion techniques for unmanned underwater vehicles (UUV). Unlike previous proposals that focus the classification on the sensors involved in the fusion, we propose a synthetic approach that is focused on the techniques involved in the fusion and their applications in UUV navigation. We believe that our approach is better oriented towards the development of sensor fusion systems, since a sensor fusion architecture should be first of all focused on its goals and then on the fused sensors

WMR navigation using local potential field corridors and narrow local occupancy grid perception

Path planning and control strategies applied to autonomous mobile robots should fulfil safety rules as well as achieve final goals. Trajectory planning applications should be fast and flexible to allow real time implementations as well as environment interactions. The methodology presented uses the on robot information as the meaningful data necessary to plan a narrow passage by using a corridor based on attraction potential fields that approaches the mobile robot to the final desired configuration. It employs local and dense occupancy grid perception to avoid collisions. The key goals of this research project are computational simplicity as well as the possibility of integrating this method with other methods reported by the research community. Another important aspect of this work consist in testing the proposed method by using a mobile robot with a perception system composed of a monocular camera and odometers placed on the two wheels of the differential driven motion system. Hence, visual data are used as a local horizon of perception in which trajectories without collisions are computed by satisfying final goal approaches and safety criteria

Local WMR navigation with monocular data

This article presents recent WMR (wheeled mobile robot) navigation experiences using local perception knowledge provided by monocular and odometer systems. A local narrow perception horizon is used to plan safety trajectories towards the objective. Therefore, monocular data are proposed as a way to obtain real time local information by building two dimensional occupancy grids through a time integration of the frames. The path planning is accomplished by using attraction potential fields, while the trajectory tracking is performed by using model predictive control techniques. The results are faced to indoor situations by using the lab available platform consisting in a differential driven mobile robot

An overview of the advantages and constraints of coded pattern projection techniques for autonomous navigation

The absolute necessity of obtaining 3D information of structured and unknown environments in autonomous navigation reduce considerably the set of sensors that can be used. The necessity to know, at each time, the position of the mobile robot with respect to the scene is indispensable. Furthermore, this information must be obtained in the least computing time. Stereo vision is an attractive and widely used method, but, it is rather limited to make fast 3D surface maps, due to the correspondence problem. The spatial and temporal correspondence among images can be alleviated using a method based on structured light. This relationship can be directly found codifying the projected light; then each imaged region of the projected pattern carries the needed information to solve the correspondence problem. We present the most significant techniques, used in recent years, concerning the coded structured light method

Using the Navigation Pane in MS Word 2010

The Navigation Pane makes it very easy to navigate around the Headings a long document, to reshuffle sections of content and to select and print parts of a file. For best viewing Download the video.

Local model predictive control for navigation of a wheeled mobile robot using monocular information

Aquesta tesi està inspirada en els agents naturals per tal de planificar de manera dinàmica la navegació d'un robot diferencial de dues rodes. Les dades dels sistemes de percepció són integrades dins una graella d'ocupació de l'entorn local del robot. La planificació de les trajectòries es fa considerant la configuració desitjada del robot, així com els vértexs més significatius dels obstacles més propers. En el seguiment de les trajectòries s'utilitzen tècniques locals de control predictiu basades en el model, amb horitzons de predicció inferiors a un segon. La metodologia emprada és validada mitjançant nombrosos experiments.

Global navigation satellite systems e a gestão do espaço aéreo

- Introdução - Sistemas actuais - Galileo - Comparação - Aplicabilidade - Futuro - Referências

Navigation assistance for wayfinding in the virtual environments: taxonomy and a survey

Efficient Navigation is essential for the user-acceptance of the Virtual Environments (VEs), but it is also inherently, a difficult task to perform. Resulting research in the area provides users with great variety of navigation assistance in VEs however it is still known to be inadequate, complex and suffers through many limitations. In this paper we discuss the task of navigation in the virtual environments and record the wayfinding assistance currently available for the VEs. The paper introduces taxonomy of navigation and categorizes the aids on basis of the functions performed. The paper provides views on current work performed in the area of non-speech auditory aids. Further we conclude by providing views on the important areas that require further investigation and research.

A novel haptic interface for navigation in large volume environments

Haptic interfaces can provide highly realistic interaction with objects within their workspace, but the task of interacting with objects over large areas or volumes is made difficult by the limits of interface travel. This paper details the development of a custom haptic interface - for navigating a large virtual environment (a simulated supermarket), and investigation into different control methods which allow for haptic interaction over extremely large workspaces.

Autonomous ship collision free trajectory navigation and control algorithms

A new autonomous ship collision free (ASCF) trajectory navigation and control system has been introduced with a new recursive navigation algorithm based on analytic geometry and convex set theory for ship collision free guidance. The underlying assumption is that the geometric information of ship environment is available in the form of a polygon shaped free space, which may be easily generated from a 2D image or plots relating to physical hazards or other constraints such as collision avoidance regulations. The navigation command is given as a heading command sequence based on generating a way point which falls within a small neighborhood of the current position, and the sequence of the way points along the trajectory are guaranteed to lie within a bounded obstacle free region using convex set theory. A neurofuzzy network predictor which in practice uses only observed input/output data generated by on board sensors or external sensors (or a sensor fusion algorithm), based on using rudder deflection angle for the control of ship heading angle, is utilised in the simulation of an ESSO 190000 dwt tanker model to demonstrate the effectiveness of the system.