891
DEVELOPING A NAVIGATION SYSTEM TO PROVIDE A ROBUST REAL TIME
POSITIONING FOR MOBILE MAPPING APPLICATION
Amir Saeed HOMAINEJAD
Independent Research Group on Geo-Spatial, Tehran, IRAN - s_homain@yahoo.com
Commission V, WG V/l
Keywords: Navigation, Real Time, Positioning, Mobile Mapping
ABSTRACT:
This is a report on recent development of a navigation system, which is used to provide real time positioning for a mobile mapping
application. The developed method is very unique and distinguished from other similar methods. An approach was designed based on
Mobile Mapping Application in order to monitor a terrain in purpose to detect an unknown object inside the terrain. Once an
unknown object was detected, position of the object was defined, and a dynamic platform was dispatched towards the object. The
dynamic platform was supplied with a vision for monitoring and navigation. A number of targets were designed and set up around
the terrain. The vision is continuously searching the targets. Once the target was recognised by the vision, the distance to the target
would be computed and according to the defined strategy the dynamic platform would be pursued its journey toward the final
destination. A stationary vision was set up on the terrain due to assist, detect, and extract any unknown objects at the terrain. This
vision was used for navigation and mapping as well. The idea behind the developing of this system was based on invention of a
system, which was able to implement a number of defined activities under Mobile Mapping application in real time without any
supervision.
1. INTRODUCTION
Introduction of new techniques and sensors to photogrammetry
at all, or to close range photogrammetry particularly, has given
an opportunity to renovate the conventional methods of
photogrammetry and create new methods. It is a great
gratefulness to other groups of sciences for their inventions and
researches, which cause to introduce a new era to
photogrammetry. Whit utilising the application of new
techniques, new terms have been materialized in
photogrammetry. Terms of Machine Vision, Robot Vision,
Videometric, Mobile Mapping, UAV, etc were unknown at late
1880s or early of 1990s, but with introduction of CCD camera,
digital image processing, introduction of a range of sensors,
techniques of remotely controlling a vehicle, and new
inventions in electronic and computer, these terms have been
gradually appeared in photogrammetry and attracted many
interests.
With increasing of demands on utilizing vision systems for
implementation of their applications on navigation,
measurement, and assessment, makes an opportunity for
photogrammetry to develop its capability in unconventional
methods. Consequently, new methods are created in order to
answer those demands; however, the new methods are involving
new issues. Particularly, the new methods have to be assessed
prior to implementation due to improving their reliability
according to requested standards. Unfortunately, the new
methods cannot be dealt like conventional methods, and for
utilising of new method, it needs to develop a strategy regarding
to methods of imagery.
Camera calibration is a critical process, which is constantly
requested to improve the reliability of photogrammetry process
and accuracy of outputs, and the mathematical modelling of
camera calibration is based on collinearity equations.
Collinearity equations have been developed based on this theory,
which all rays emitted or reflected from an object are travelling
in straight lines and will converge on the principle point of a
camera and then they will diverge to make an image of the
object on a plan behind the camera. Camera calibration for
aerial photogrammetry and conventional photogrammetry can
be fulfilled once prior or after of image acquiring. Aerial and
conventional photogrammetry is using stereo imagery and the
elevations of all images are roughly equal, once camera
calibration’s parameters were computed, they can be used for
all images. In contrast, at non-conventional photogrammetry the
distances of objects from camera are not equal, the depth of
view is dramatically changing as well as baseline, and
consequently camera calibration’s parameters are changing
from one image to another image. Therefore, it is very
important to update all elements of camera calibration at the
time of imagery. It is the most disadvantages for a close range
photogrammetric project due to computing camera calibration
in this quantity. In some cases self-calibration has been advised
Fraser et al (1995), Fryer (1996), but self-calibration does not
exclude this amount of calibration and the issue still remains. In
some cases, pre-calibration and post-calibration have been
recommended El-Hakim (1996), Shortis et al (1995), but this
strategy includes some issues, which declines the reliability of
whole process.
This paper is a report on developing a method of navigation
based on Mobile Mapping at real time. A system consists of
vision system, image processing, and server. Two vision
systems have been employed; the first one has had stationary
position, and the second one is set up on a dynamic platform.
The stationary vision system is designed to monitor the terrain
for detecting any object and navigation purpose. The second
vision system is used for navigation. Images of the stationary
vision are downloaded on a map of the terrain in order to
position of and object on the terrain according to the map.
Indeed, the map has been used for positioning of any object on
the terrain. The map can be updated time by time, but not in a
very large amount. Only limited information has been amended