Modern robotics has a great approach to science fiction robots that seem to navigate accurately and effortlessly. Despite major advances in mobile robotics navigation, the fact is that navigation is a major problem for research and can be approached in several ways. In fact, you only have to answer the basic question "where am I?".
Autonomous navigation is truly a serious challenge for robotics and all the sciences transverse to this. We use the term "localization" to refer to the process of determining the position of a robot using information from external sensors. The location provides important information for the process of navigation. Our research has focused on the provision of this possibility through the use of ultrasonic detection sensors to provide the system that directs the robot, all the necessary information from the environment, requiered for the process of navigation.
The navigation problem
Stated most simply, the problem of navigation can be summarized by the following three questions:
where am I? - this is about localization, how can a robot work out where it is in a given environment, based on the information given by the sensors.
where am I going?
The second and third questions are essentially those of specifying a goal and being able to plan a path. Investigations of the latter two questions usually come under the domain of path planning [1] and obstacle avoidance [2], [3]. For the FIC project, we are principally concerned with the second an third questions, about navigation.
The problem of position determination has been of vital importance throughout the history of mobile robotics [6]. The process of distance measurement, correlation, and triangulation is vital to build and maintain quite accurate maps. Navigation is a well-understood quantitative science, used routinely in maritime, aviation, and space applications. Given this, the question must be asked why robust and reliable autonomous mobile robot navigation remains such a dificult problem.
In our view, the reason for this is that the navigation process itself is a problem. The reliable acquisition or extraction of information about navigation beacons, from sensor information, and the automatic correlation or correspondence of these with some navigation map that makes the autonomous navigation problem so dificult.
Implementing a navigation system that uses artificial beacons together with sensors that provide accurate and reliable measurements of beacon location is a straightforward procedure used by many commercial and industrial robots today. For example, the GEC Caterpillar automatic guided vehicle (AGV) uses a rotating laser to locate itself with respect to a set of bar-codes that are fixed at known locations through the AGV's environment [8].
The goal of our research is to achieve comparable performance to artificial beacon systems without modifying the environment, by sensing the naturally-occurring geometry of typical indoor scenes. This competence of localization would provide a mobile robot with the ability to determine its position without help, such as bar-code markers on the walls. While a limited form of this competence might use hand-measured maps of the environment provided a priori to the robot, completely autonomous operation will require that the robot construct and maintain its own map in a changing environment (dynamic map building). At the moment, we are working to get dynamic map building and maintenance [12], [13] and state our goal as the development of an autonomous system [14] that can:
build a large-scale, metrically accurate map of a static, people-free environment [15] and
use this map for localization at arbitrary locations within the environment.[16]
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Extrated from http://cml.mit.edu/~jleonard/pubs/ldw_kluwer1992.pdf
Parts of the text belong to Trajectory generation and FIC project.