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“We are always looking for animals with unusual abilities, ones that do something better than humans,” said Saptarshi Das, assistant professor of engineering science and mechanics at Pennsylvania State University. “Insect vision is something people use regularly to design automatic systems because they fly and don't collide, but then we found locusts are unique.”
Locusts are unusual, the team said, because they use a single, specialised neuron called the Lobula Giant Movement Detector (LGMD) to avoid collisions.
“We started looking at how it works and locusts are just incredible,” said Das. “What these creatures can do is very humbling.”
According to Darsith Jayachandran, graduate student in engineering science and mechanics, the neuron receives two different signals. An image of an approaching locust falls on the avoiding locust's eye. The closer the invading locust gets, the larger the image and the stronger the excitation signal becomes. The other input is the change in angular velocity of the invading locust, with respect to the avoiding locust.
“Because the neuron has two branches, the locust computes the changes in these two inputs and realises that something is going to collide,” said Jayachandran. “So the avoiding locust changes direction.”
The researchers developed a compact, nanoscale collision detector using a photodetector made of monolayer molybdenum sulphide. They placed the photo detector on top of a programmable ‘floating gate’ memory architecture, which can mimic the locust's neuron response using only a tiny amount of energy.
The team called the detector “a leap forward towards the development of smart, low-cost, task-specific, energy efficient and miniaturised collision-avoidance systems.”
Locusts move at 2-3mph and make directional changes in hundreds of milliseconds. The decision to move employs non-linear mathematics and a minuscule energy expenditure, the researchers said.
This quick reaction and modest energy use is attractive for mechanised collision detectors. Current detectors for autonomous cars are large and heavy. The researchers' collision detector responds in two seconds, so would need to make quicker calculations for practical use in vehicles.
The photodetector causes an increase in device current in response to an oncoming object – the excitatory signal – while the underlying programmable memory stack always causes a decrease in the current – the inhibitory signal. When an object approaches, the excitatory signal is added to the inhibitory stimuli, causing a change in the device current and mimicking the escape response of the LGMD neuron found in locusts.
“While locusts can only avoid collisions with other locusts, our device can detect potential collisions of a variety of objects at varying speeds,” said Das.
The researchers have only tested the device with objects on a direct collision path, and need to optimise the responses for additional situations.
“We can't do every measurement, every situation,” said Aaryan Oberoi, graduate student in engineering science and mechanics. “So we developed a numerical model. We can also test if multiple devices on the same chip would work better. So far, it looks like a single device will be sufficient. However, a multi-pixel collision detector array can offer collision avoidance in 3D space.”
The work was reported in Nature Electronics.
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