Position calculation for AGVs using incomplete information.
Report 2007.TEL.7124, Transport Engineering and Logistics.
In the AGV laboratory of Transport Engineering of the Faculty Mechanical
Engineering at the Technical University of Delft, scale models of AGVs are
tested. All Automated Guide Vehicles are equipped with an on-board
controller, which controls the drive engines and steering servos. The test
field is equipped with and overhead camera system to determine the positions
of the AGVs in the field. A computer, using image recognition techniques,
decodes the camera images and periodically sends the AGVs their locations
via a wireless network.
The allocation of the AGV, from the camera snapshot through the processing
of the images to the transmission of data over the network, takes a certain
amount of time. This time-delay causes a deviation between the measured
location and the actual location of the AGV, which leads to a less accurate
controllability of the AGV.
This paper describes the research for a concept to improve the accuracy of
position-data received by the AGV.
Principle for compensation
The accuracy of the received position-information will be improved by using
the dead-reckoning principle for compensating the position: The updated
position-information, the AGV periodically receives, can be seen as the most
recent, known position of the AGV. This position is used as a starting point
from which an extrapolation of the AGVs movement is calculated, on the basis
of actual speed and heading.
The extrapolation of the AGVs trajectory is done by simulation. A vehicle
model of the AGV is used for this purpose. This model includes the geometric
properties of the AGV plus the electrical en mechanical properties of the
actuators. All parameters have to be accurately calibrated for the corrector
model behavior. The vehicle model will be controlled using the same signals
that the onboard controller of the AGV uses to drive the actuators. Therefore
these controller signals are stored for future reference.
The results of the extrapolation of the AGVs trajectory are predicted to
give a more accurate representation of the actual location of the AGV at a
given moment. The algorithm that calculates the extrapolation will be added
to the software of the on-board controller, and is designated in this
report as the Corrector.
To further investigate the implementation of the described principle, a
TOMAS/Delphi simulation model is written. In this simulation environment one
AGV, the positioning system and the Corrector are simulated. The AGV is
programmed to run a specified trajectory. The positioning system 'reads' the
position of this AGV at a predefined interval. It holds this position for
some time, to simulate the time-delay, before it offers the position-data to
the Corrector. The corrector then uses this information to extrapolate the
trajectory. The deviation between the extrapolated trajectory and the real
actual position of the AGV is the key performance parameter for the Corrector.
Several experiments have been done to test the Corrector. The first tests are
for the purpose of verification of the simulation model. The following
experiments are done to test the influence of variations in some parameters on
the behavior of the model.
An important factor is the level of accuracy in which the time-delay of the
positioning system can be estimated. Currently, this accuracy is not known
for the laboratory setup. This factor is therefore ignored by setting
time-delays to a known constant. There are no experiments done to analyze
the sensitivity of the model for this factor.
First, the level of accuracy in determining the initial state of the AGV is
a relevant factor for performance. (Speed and steering angle are unknowns,
since the positioning system can only measure position and orientation.)
The last factor is the operating frequency of the Corrector and positioning
Secondly, the quality of the extrapolation of movement is largely affected
by the accuracy of the parameters of the vehicle model. Experiments are
conducted to determine the influence of the various parameters.
Conclusion and recommendations
From the experiments it can be concluded that with the right settings, the
corrector is able to improve position information. Because of the fact that
all experiments were conducted within a simulation model, it is not possible
to make a statement on the improvement that this corrector system will bring
when implemented in AGV laboratory environment. It is possible to draw some
conclusions on the sensitivity of the corrector for deviations in certain
parameters: The correctness of the estimation of the initial state of the
AGV at the beginning of an extrapolation trajectory has an influence on the
overall performance of the Corrector. Using the steering signals that were
given before the positioning snapshot could decrease this effect.
The vehicle model, especially the model of the drive motors, is in the
current form very sensitive for errors. This model will have to be
calibrated very carefully to achieve good Corrector results.
To enhance the correction method it is recommended to further investigate the
possibility of using more position data than just the most recent one. The
combined weighted average of multiple extrapolations could then be used to
give an improved result.
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