A Low-Cost Real-Time Spiking System for Obstacle Detection based on Ultrasonic Sensors and Rate Coding
Since the advent of mobile robots, obstacle detection has been a topic of great interest. It has also been a subject of study in neuroscience, where flying insects and bats could be considered two of the most interesting cases in terms of vision-based and sound-based mechanisms for obstacle detectio...
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Main Authors | , , , , |
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Format | Journal Article |
Language | English |
Published |
04.09.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Since the advent of mobile robots, obstacle detection has been a topic of
great interest. It has also been a subject of study in neuroscience, where
flying insects and bats could be considered two of the most interesting cases
in terms of vision-based and sound-based mechanisms for obstacle detection,
respectively. Currently, many studies focus on vision-based obstacle detection,
but not many can be found regarding sound-based obstacle detection. This work
focuses on the latter approach, which also makes use of a Spiking Neural
Network to exploit the advantages of these architectures and achieve an
approach closer to biology. The complete system was tested through a series of
experiments that confirm the validity of the spiking architecture for obstacle
detection. It is empirically demonstrated that, when the distance between the
robot and the obstacle decreases, the output firing rate of the system
increases in response as expected, and vice versa. Therefore, there is a direct
relation between the two. Furthermore, there is a distance threshold between
detectable and undetectable objects which is also empirically measured in this
work. An in-depth study on how this system works at low level based on the
Inter-Spike Interval concept was performed, which may be useful in the future
development of applications based on spiking filters. |
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DOI: | 10.48550/arxiv.2409.02680 |