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regardless the relative position of the nearby objects.
The increase in the number of false positives to
higher velocities is based on the fact that, at higher
velocities, the difference between successive frames
is higher, leading to the production of high
excitation levels and, consequently, a bigger number
of collision detection alarms.
Although the difference verified in relation to
correct collision detections between different
velocities, the results obtained are very satisfactory, as
the number of correct detections are always higher
than the sum of missed and false positive detections.
4 CONCLUSIONS
In this paper, we propose a modified LGMD model
based on the identified LGMD neuron of the locust
brain. The model proved to be a robust collision
detector for autonomous robots. This model has a
mechanism that favours grouped excitation, as well as
two cells with a particular behaviour that provide
additional information on the depth direction of
movement.
For applications as collision detectors in
robotics, the model proposed is able to remove the
noise captured by the camera, as well as enhance its
ability to recognize the direction of the object
movement and, by this way, remove the false
collision alarms produced by the previous models
when a nearby object is moving away.
Experiments with a DRK8000 robot showed that
with these two new
procedures, the robot was able to
travel autonomously in real time and within a real
arena.
The results illustrate the benefits of the LGMD
based neural network here proposed, and, in the
future, we will continue to use and enhance this
approach, using, for that, a combination of
physiological and anatomical studies of the locust
visual system, in order to improve our understanding
about the relation between the LGMD neuron output
and the locust muscles related to the avoidance
manoeuvres.
ACKNOWLEDGEMENTS
Work supported by the Portuguese Science
Foundation (grant PTDC/EEA-CRO/100655/2008).
Ana Silva is supported by PhD Grant
SFRH/BD/70396/2010, granted by the Portuguese
Science Foundation.
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